Robust Reggresion with M-Estimation

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Regresi Robust dengan M-Estimation

Regresi robust diperkenalkan Andrews (1972) dalam Ryan (1997). Metode ini merupakan alat penting untuk menganalisis data yang dipengaruhi oleh outlier untuk menghasilkan model yang robust atau resistant terhadap outlier. Suatu estimasi yang resistant adalah relatif tidak terpengaruh oleh perubahan besar pada bagian kecil data atau perubahan kecil pada bagian besar data. Prosedur robust ditujukan untuk mengakomodasi adanya keanehan data, sekaligus meniadakan identifikasi adanya data outlier dan juga bersifat otomatis dalam menanggulangi data outlier (Aunuddin, 1989). Chen (2002) menyebutkan beberapa prosedur estimasi parameter dalam regresi robust, dua diantaranya adalah M-Estimation yang diperkenalkan Huber (1973) dan Least Trimmed Squares (LTS) yang diperkenalkan oleh Rousseeuw (1984).

M-Estimation merupakan metode regresi robust yang sering digunakan. M-Estimation dipandang baik untuk mengestimasi parameter yang disebabkan oleh x-outlier dan memiliki breakdown point 1/n. M-Estimation meminimumkan fungsi objektif :

        

             = (2.8)

Nilai diperoleh melalui iterasi (Chen, 2002) :

              (2.9)

dengan l (l = 1, 2,…) adalah iterasi, = dan adalah invers fungsi komulatif normal standart.

adalah fungsi simetris dari residual atau fungsi yang memberikan kontribusi pada masing-masing residual pada fungsi objektif.

dengan derivatif dari , maka untuk meminimumkan persamaan (2.8) :

                  (2.10)

merupakan fungsi influence yang digunakan dalam mem-peroleh bobot (weight). Dengan fungsi pembobot maka persamaan (2.10) menjadi:

                  (2.11)

Persamaan (2.11) dinotasikan ke dalam matrik :

                  (2.12)

Persamaan (2.12) disebut weighted least squares yang memini-mumkan . Weighted least squares dapat diguna-kan untuk mendapatkan M-estimation, sehingga estimasi para-meter menjadi :

              (2.13)

Pembobot dalam M-estimation bergantung pada residual dan koefisien. Fox (2002) menyatakan untuk menyelesaikan masalah tersebut perlu dilakukan prosedur iterasi yang disebut iteratively reweighted least squares (IRLS) seperti pada Gambar 3.4.

Tiga bentuk M-Estimation diantaranya estimasi least square, Huber dan Tukey bisquare (biweight). Bentuk fungsi objektif, fungsi influence dan fungsi pembobot untuk ketiga jenis M-Estimation dapat dilihat di Tabel 2.1. M-estimation Least Square dengan merupakan metode OLS. M-estimation Huber melalui fungsi melibatkan pengkuadratan residual yang kecil seperti pada OLS tetapi memberkan residual yang besar sedemikian rupa untuk mengurangi pengaruhnya (Myers, 1990).

Nilai r pada fungsi objektif, influence dan pembobot (Tabel 2.1) adalah tunning constant. Kuzmic et.al (2004) menyebutkan M-estimation Huber efektif digunakan pada α = 5% dengan r=1,345, sedangkan M-estimation Tukey Bisquare dengan r=4,685. Kelly (2008) menyatakan permasalahan dalam estimasi regresi robust adalah perlu dilakukan pemilihan tunning constant agar estimasi yang diperoleh lebih spesifik dan memimimumkan jumlah kuadrat residual. Menurunkan tunning constant akan menaikan pembobot terhadap residual yang besar. Menaikkan tunning constant akan menurunkan pembobot terhadap residual yang besar. Semakin besar r maka estimasi robust akan mendekati least square. Grafik perbandingan fungsi objektif, fungsi influence dan fungsi pembobot pada M-estimation dapat dilihat pada Gambar 2.1. Grafik tersebut menggunakan r = 1,345 untuk M-estimation Huber dan r = 4,685 untuk M-estimation Tukey Bisquare dengan = 1.

Tabel 2.1 Fungsi objektif, fungsi influence, dan fungsi pembobot pada M-estimation

Metode

Least Square

Huber

Tukey Bisquare

Fungsi objektif

Fungsi influence

Fungsi Pembobot

Sumber : Fox (2002), Mongomery (1992)



Sumber : Fox (2002)

Gambar 2.1 Fungsi objektif, fungsi influence, dan fungsi pembobot pada M-estimation.

Algoritma yang digunakan adalah IRLS (Gambar 3.4), tahapanya :

  1. Menaksir parameter dengan menggunakan persamaan 2.5 dan didapatkan residual ei,0.
  2. Menentukan dan fungsi pembobot
  3. Mencari estimasi pada iterasi l ( l = 1, 2, … ) dengan weighted least square.

            

    dengan merupakan matrik diagonal dengan elemen diagonalnya adalah . Sehingga estimasi parameter pada iterasi pertama ( l = 1 ) menggunakan ei,0 dan .

  4. Mengulang tahap 2 dan 3 hingga didapatkan penaksiran parameter yang konvergen.

Fungsi pembobot untuk M-Huber adalah


dan Tukey Bisquare adalah


Berikut adalah diagram alur pembentukan model M – estimation :


Gambar 3.4 Diagram Alur Permodelan dengan M-Estimation

Pengujian Parameter Model

    Pengujian parameter dalam model regresi bertujuan untuk mengetahui apakah parameter tersebut telah menunjukkan hubungan yang nyata antara variabel prediktor dan variabel respon. Disamping itu juga untuk mengetahui kelayakan parameter dalam menerangkan model. Terdapat dua tahap pengujian yaitu uji serentak dan uji parsial (individu).

  1. Uji Serentak

    Uji serentak merupakan pengujian secara bersama semua parameter dalam model regresi. Hipotesis yang digunakan adalah sebagai berikut :

H0 :
b0
=
b1 = … = bj = 0

H1 : paling tidak ada satu bj
¹ 0, j = 0, 1, … k

Statistik uji yang digunakan untuk OLS adalah

    Fhitung =     =      (3.2)

Sedangkan untuk Weighted least squares (WLS)

    Fhitung(weighted) =

          =      (3.3)

    Ket : MSR : Mean Square Regression


MSE : Mean Square Error

    Pengambilan keputusan adalah apabila Fhitung
> Fa (k, n-k-1) dengan k adalah parameter maka H0 ditolak pada tingkat signifikansi a, artinya paling sedikit ada satu bj yang tidak sama dengan nol. Pengambilan keputusan juga dapat melalui P-value dimana H0 ditolak jika P-value < α.

  1. Uji Parsial

    Uji parsial merupakan pengujian secara individu parameter dalam model regresi yang bertujuan untuk mengetahui parameter model regresi telah signifikan atau tidak. Hipotesis yang digunakan adalah sebagai berikut :

    H0 :
bj
= 0

    H1 : bj
¹ 0, j = 0, 1, 2, …, k

Statistik uji yang digunakan untuk metode OLS adalah

                       (3.4)

dengan

          (3.5)

Sedangkan untuk metode Weighted least squares (WLS)

                  (3.6)

dengan merupakan diagonal matrik kovarian.

Pengambilan keputusannya yaitu apabila |thitung| > t(1-a/2, n-k-1) dengan k adalah parameter maka H0 ditolak pada tingkat signifikansi a, artinya ada pengaruh xi terhadap model. Pengambilan keputusan juga dapat melalui P-value, dimana H0 ditolak jika P-value < α.

SPSS for Windows

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A brief tutorial


This tutorial is a brief look at what SPSS for Windows is capable of doing. Examples will come from Statistical Methods for Psychology by David C. Howell. It is not our intention to teach you about statistics in this tutorial. For that you should rely on your classes in statistics and/or a good textbook. If you’re a novice this tutorial should give you a feel for the programme and how to navigate through the many options. Beyond that, the SPSS Help Files should be used as a resource. Further, SPSS sells a number of very good manuals.

The Basics

SPSS for Windows has the same general look a feel of most other programmes for Windows. Virtually anything statistic that you wish to perform can be accomplished in combination with pointing and clicking on the menus and various interactive dialog boxes. You may have noted that the examples in the Howell textbook are performed/analyzed via code. That is, SPSS, like many other packages, can be accessed by programming short scripts, instead of pointing and clicking. We will not cover any programming in this tutorial.

Presumeably, SPSS is already installed on your computer. If you don’t have a shortcut on your desktop go to the [Start => Programs] menu and start the package by clicking on the SPSS icon.

Before proceeding I should say a few words about a very simple convention that will be used in this tutorial. In this point and click environment one often has to navigate through many layers of menu items before encountering the required option. In the above paragraph the prescribed task was to locate the SPSS icon in the [Start] menu structure. To get to that icon, one must first click on [Start] then move the pointer to the[Programs] options, before locating the SPSS icon. This sequence of events can be conveyed by typing [Start => Programs] . That is, one must move from the outer layer of the menu structure to some inner layer in sequence….

Now, back to the tutorial.

Once you’ve clicked on the SPSS icon a new window will appear on the screen. The appearance is that of a standard programme for windows with a spreadsheet-like interface.


As you can see, there are a number of menu options relating to statistics, on the menu bar. There are also shortcut icons on the toolbar. These serve as quick access to often used options. Holding your mouse over one of these icons for a second or two will result in a short function description for that icon. The current display is that of an empty data sheet. Clearly, data can either be entered manually, or it can be read from an existing data file.

Browsing the file menu, below, reveals nothing too surprising – many of the options are familiar. Although, the details are specific to SPSS. For example, the [New] option is used to specify the type of window to open. The various options, under the [New] heading are,

  • [Data] Default window with a blank data sheet ready for analyses
  • [Syntax] One can write scripts like those present in the Howell text, instead of using the menus. See the SPSS manuals for help on this topic.
  • [Output] Whenever a procedure is run, the out is directed to a separate window. One can also have multiple [Output] windows open to organize the various analyses that might be conducted. Later, these results can be saved and/or printed.
  • [Script] This window provides the opportunity to write fullblown programmes, in a BASIC-like language. These programmes have access to functions that make up SPSS. With such access it is possible to write user-defined procedures – those not part of SPSS – by taking advantage of the SPSS functions. Again, this is beyond the scope of this tutorial.


Also present in the [File] menu are two separate avenues for reading data from existing files. The first is the [Open] option. Like other application packages (e.g., WordPerfect, Excel, ….) SPSS also has it’s own format for saving data. In this case, the accepted extension for any file saved using the proprietary format is “sav”. So, one can have a datafile saved as “data1.sav”. Anyways, this format is not readable with a text editor, it is a binary format. The benefits are that all formatting changes are maintained and the file can be read faster, hence the [Open] option. It is specifically meant for files saved in the SPSS format. The second option, [Read ASCII Data], as the name suggests is to read files that are saved in ASCII format. As can be seen, there are two choices – [Freefield] and [Fixed Columns]. Clicking on one of these options will produce a dialog box. One must specify a number of parameters before a file can be read successfully.


Reading ASCII files requires that the user know something about the format of the data file. Otherwise, one is likely get stuck in the process of reading, or the result may be a costly error. The more restrictive format is[Fixed Columns]. One must know how many variables there are, whether a variable is in numeric or string format, and the first and last column of each variable. For example, think of the following as an excerpt from an ASCII datafile.


male     37 102

male     22 115

male     27 99

…. .. …

female 48 107

female 21 103

female 28 122

…… .. …


An examination of the datafile provides several key pieces of information,

  • There are 3 variables
  • Variable 1 is a string , Variable 2 and 3 are numeric
  • Variable 1: first column=1, last column=6
    • Notice that none of the columns overlap. The longest case for column one is the name “female”, that spans from the first column to the sixth – or, the letter e. As you can see, one has to manually locate the first and last column, of each variable.
  • Variable 2: first column=9, last column=10
  • Variable 3: first column=12, last column=14

One needs all of the above information, in addition to, name for each of the three variables. It is a highly structured way of setting up and describing the data. For such files I would suggest becoming comfortable with a good text editor. Failing that, you may wish to try Notepad or WordPad in Win95, but ensure that you save as a textfile with WordPad. A fullfledged word processor like Word or WordPerfect will also work provided that you remember to save as a textfile. These same editors will allow you to figure out the column locations for each of the variables.

The [Freefield] option is less restrictive. Essentially, the columns can be ragged (i.e., overlapping). One need only preserve the order of each variable across all of the cases.


male 37 102

male 22 115

male 27 99

…. .. …

female 48 107

female 21 103

female 28 122

…… .. …


Experiment with creating datafiles and reading them with this method. As for the SPSS format, there are a large number of sample datafiles included in your package. Just click on [Open] and find the SPSS home directory. Make sure the filetype in the dialog box associated with [Open] is set to “*.sav” – the default…

Before we move onto actual data, click on [Statistics] . The menu that appears reveals many classes of statistics available for use. Each class is further subdivided into other options, as denoted by the little arrow at the right size of the menu selector. Explore what is offered by moving your mouse over the various procedures listed.


Data


To begin the process of adding data, just click on the first cell that is located in the upper left corner of the datasheet. It’s just like a spreadsheet. You can enter your data as shown. Enter each datapoint then hit [Enter]. Once you’re done with one column of data you can click on the first cell of the next column.

These data are taken from table2.1 in Howell’s text. The first column represents “Reaction Time in 100ths of a second” and the second column indicates “Frequency”.


If you’re entering data for the first time, like the above example, the variable names will be automatically generated (e.g., var00001, var00002,….). They are not very informative. To change these names, click on the variable name button. For example, double click on the “var00001” button. Once you have done that, a dialog box will appear. The simplest option is to change the name to something meaningful. For instance, replace “var00001” in the textbox with “RT” (see figure below).


In addition to changing the variable name one can make changes specific to [Type], [Labels], [Missing Values], and [Column Format].

  • [Type] One can specify whether the data are in numeric or string format, in addition to a few more formats. The default is numeric format.


  • [Labels] Using the labels option can enhance the readability of the output. A variable name is limited to a length of 8 characters, however, by using a variable label the length can be as much as 256 characters. This provides the ability to have very descriptive labels that will appear at the output.

    Often, there is a need to code categorical variables in numeric format. For example, male and female can be coded as and 2, respectively. To reduce confusion, it is recommended that one usesvalue labels . For the example of gender coding, Value:1 would have a correspoding Value label: male. Similarly, Value:2 would be coded with Value Label: female. (click on the [Labels] button to verify the above)

  • [Missing Values] See the accompanying help. This option provides a means to code for various types of missing values.
  • [Column Format] The column format dialog provides control over several features of each column (e.g., width of column).

The next image reflects the variable name change.


Once data has been entered or modified, it is adviseable to save. In fact, save as often as possible [File => SaveAs].


SPSS offers a large number of possible formats, including their own. A list of the available formats can be viewed and selected by clicking on the Save as type: , on the SaveAs dialog box. If your intention is to only work in SPSS, then there may be some benefit to saving in the SPSS(*.sav) format. I assume that this format allows for faster reading and writing of the data file. However, if your data will be analyzed and looked by other packages (e.g., a spreadsheet), it would be adviseable to save in a more universal format (e.g., Excel(*.xls), 1-2-3 Rel 3.0 (*.wk3).

Once the type of file has been selected, enter a filename, minus the extension (e.g., sav, xls). You should also save the file in a meaningful directory, on your harddrive or floppy. That is, for any given project a separate directory should be created. You don’t want your data to get mixed-up.


The process of reading already saved data can be painless if the saved format is in the SPSS or a spreadsheet format. All one has to do is,

  • click on [File => New => Data]


  • click on [File => Open] : a dialog box will appear
  • navigate to desired directory using the Look in: menu at the top of the dialog box
  • select file type in the Files of type menu
  • click on the filename that is needed.

The process of reading existing files is slightly more involved if the format is ASCII/plain text (see the earlier description of [Freefield] and [Fixed Columns]). As an example, the ASCII data from table2.1 in the Howell text will be used. A file containing the data should be included in the accompanying disk for the text. [Note: It was not present in my disk, so I downloaded the file from Howell’s webpage.] I’ve placed the files on my harddrive at c:\ascdat. In the case of this set of data,there are four columns representing observation number, reaction time, setsize, and the presence or absence of the target stimulus. This information can be found in thereadme.txt file that is also on the disk. Typically, we are aware of the contents of our own data files, however, it doesn’t hurt to keep a record of the contents of such files.

To make life easier the [File => Read ASCII Data => Freefield] will be used.


The resulting dialog box requires that a File , a Name and a Data Type be specified for each variable, or column of data. The desired file is accessed by clicking on the [Browse] button, and then navigating to the desired location. Since the extension for the sought after file is dat there is no need to change the Files of type: selection. However, if the extension is something else (e.g., *.txt) then it would be necessary to select All files(*.*) from the Files of type: menu. Since there are 4 variables in this data set, 4 names with the corresponding type information must be specified. To Add the first variable, observations, to the list,

  • type “obs” in the Name box
  • the Data Type is set to Numeric by default. If “obs” was a string variable, then one would have to click on String
  • click on the Add button to include this variable to the list.
  • repeat the above procedure with new names and data types for each of the remaining variables. It is important that all variables be added to the list. Otherwise, the data will be scrambled.

(Please explore the various options by clicking on any accessible menu item.)


The resulting data files appears in the data editor like the following.


The next section will cover some descriptive statistics.

Descriptive Statistics


We can replicate the frequency analyses that are described in chapter 2 of the text, by using the file that was just read into the data editor – tab2-1.dat. These analyses were conducted on the reaction time data. Recall, that we have labelled this data as RT.

To begin, click on [Statistics=>Summarize=>Frequencies]….


The result is a new dialog box that allows the user to select the variables of interest. Also, note the other clickable buttons along the border of the dialog box. The buttons labelled [Statistics…] and [Charts…] are of particular importance. Since we’re interested in the reaction time data, click on rt followed by a mouse click on the arrow pointing right. The consequence of this action is a transference of the rt variable to the Variableslist. At this point, clicking on the [OK] button would spawn an output window with the Frequency information for each of the reaction times. However, more information can be gathered by exploring the options offered by the [Statistics…] and [Charts…].


[Statistics…] offers a number of summary statistics. Any statistic that is selected will be summarized in the output window.


As for the options under [Charts…] click on Bar Charts to replicate the graph in the text.


Once the options have been selected, click on [OK] to run the procedure. The results are then displayed in an output window. In this particular instance the window will include summary statistics for the variable RT, the frequency distribution, and the frequency distribution. You can see all of this by scrolling down the window. The results should also be identical to those in the text.



You may have gathered from the above that calculating summary statistics requires nothing more than selecting variables, and then selecting the desired statistics. The frequency example allowed us to generate frequency information plus measures of central tendencies and dispersion. These statistics can be had by clicking directly on [Statistics=>Summarize=>Descriptives]. Not surprisingly, another dialog box is attached to this procedure. To control the type of statistics produced, click on the [Options…] button. Once again, the options include the typical measures of central tendency and dispersion.

Each time as statistical procedure is run, like [Frequencies…] and [Descriptives…] the results are posted to an Output Window. If several procedures are run during one session the results will be appended to the same window. However, greater organization can be reached by opening new Output windows before running each procedure – [File=>New=>Output]. Further, the contents of each of these windows can be saved for later review, or in the case of charts saved to be later included in formattted documents. [Explore by left mouse clicking on any of the output objects (e.g., a frequency table, a chart, …) followed by a right button click. The left left button click will highlight the desired object, while the right button click will popup a new menu. The next step is to click on the copy option. This action will store the object on the clipboard so that it can be pasted to Word for Windows document, for example…..]

Chi-Square & T-Test


The computation of the Chi-Square statistic can be accomplished by clicking on [Statistics => Summarize => Crosstabs…]. This particular procedure will be your first introduction to coding of data, in the data editor. To this point data have been entered in a column format. That is, one variable per column. However, that method is not sufficient in a number of situations, including the calculation of Chi-Square, Independent T-tests, and any Factorial ANOVA design with between subjects factors. I’m sure there are many other cases, but they will not be covered in this tutorial.  Essentially, the data have to be entered in a specific format that makes the analysis possible.  The format typcially reflects the design of the study, as will be demonstrated in the examples.

In your text, the following data appear in section 6.????. Please read the text for a description of the study. Essentially, the table – below – includes the observed data and the expected data in parentheses.

 

Fault Guilty Not Guilty Total
Low 153(127.559) 24(49.441) 177
High 105(130.441) 76(50.559) 181
Total 258 100 358

In the hopes of minimizing the load time for remaining pages,  I will make use of the built in table facilty of HTML to simulate the Data Editor in SPSS. This will reduce the number of images/screen captures to be loaded.

For the Chi-Square statistic, the table of data can be coded by indexing the column and row of the observations.  For example, the count for being guilty with Low fault is 153.  This specific cell can be indexed as coming from row=1 and column=1.  Similarly, Not Guilty with High fault is coded  as row=2 and column=2.  For each observation, four in this instance, there is unique code for location on the table.  These can be entered as follows,

 

Row

Column

Count

1

1

153

1

2

24

2

1

105

2

2

76

  • So, 2 rows * 2 columns equals 4 observations.  That should be clear.
  • For each of the rows, there are 2 corresponding columns, that is reflected in the Count column.  The Count column represents the number of time each unique combination Row and Column occurs.

The above presents the data in an unambigous manner.  Once entered, the analysis is a matter of selecting the desired menu items, and perhaps selecting additional options for that statistic.  [Don’t forget to use the labelling facilities, as mentioned earlier, to meaningfully identify the columns/variables.  The labels that are chosen will appear in the output window.]

To perform the analysis,

  • The first step is to inform SPSS that the COUNT variable represents the frequency for each unique coding of ROW and COLUMN, by invoking the WEIGHT command. To do this, click on [Data => Weight Cases]. In the resultant dialog box, enable the Weight cases by option, then move the COUNT variable into the Frequency Variable box. If this step is forgotten, the count for each cell will be 1 for the table.


  • Now that the COUNT variable has been processed as a weighted variable, select [Statistics => Summarize => Crosstabs…] to launch the controlling dialog box.
  • At the bottom of the dialog box are three buttons, with the most important being the [Statistics…] button. You must click on the [Statistics…] button and then select the Chi-square option, otherwise the statistic will not be calculated. Exploring this dialog box makes it clear that SPSS can be forced to calcuate a number of other statistics in conjuction with Chi-square. For example, one can select the various measures of association (e.g., contingency coefficient, phi and cramer’s v,…), among others.
  • Move the ROW variable into the Row(s): box, and the COLUMN variable into the Column(s):, then click [OK] to perform the analysis. A subset of the output looks like the following,


Although simple, the calculation of the Chi-square statistic is very particular about all the required steps being followed. More generally, as we enter hypothesis testing, the user should be very careful and should make use of manuals for the programme and textbooks for statistics.


T-tests

By now, you should know that there are two forms of the t-test, one for dependent variables and one for independent variables, or observations. To inform SPSS, or any stats package for that matter, of the type of design it is necessary to have to different ways of laying out the data. For the dependent design, the two variables in question must be entered in two columns. For independent t-tests, the observations for the two groups must be uniquely coded with a Gruop variable. Like the calculation of the Chi-square statistic, these calculations will reinforce the practice of thinking about, and laying out the data in the correct format.

Dependent T-Test

To calculate this statistic, one must select [Statistics => Compare Means => Paired-Samples T Test…] after enterin the data. For this analysis, we’ll use the data from Table 7.3, in Howell.

  • Enter the data into a new datafile. Your data should look a bit like the following. That is, the two variables should occupy separate columns…
Mnths_6

Mnths_24

124

114

94

88

115

102

110

2

116

2

139

2

116

2

110

2

129

2

120

2

105

2

88

2

120

2

120

2

116

2

105

2

123

132

Note that the variable names start with a letter and are less than 8 characters long. This is a bit constraining, however, one can use the variable label option to label the variable with a longer name. This more descriptive name will then be reproduced in the output window.

  • To calculate the t statistic click on [Statistics => Compare Means => Paired-Samples T Test…], then select the two variables of interest. To select the two variables, hold the [Shift] key down while using the mouse for selection. You will note that the selection box requires that variables be selected two at a time. Once the two variables have been selected, move them to the Paired Variables: list. This procedure can be repeated for each pair of variables to be analyzed. In this case, select MNTHS_6 and MNTHS_24 together, then move them to the Paired Variables list. Finally, click the [OK] button.

    The critical result for the current analysis will appear in the output window as follows,


    As you can see an exact t-value is provided along with an exact p-value, and this p-value is greater that the expected value of 0.025, for a two-tailed assessment. Closer examination indicates several other statistics are presented in output window.

Quite simply, such calculations require very little effort!

Independent T-tests

When calculating an independent t-test, the only difference involves the way the data are formatted in the datasheet. The datasheet must include both the raw data and group coding, for each variable. For this example, the data from table 7.5 will be used. As an added bonus, the number of observations are unequal for this example.

Take a look at the following table to get a feel for how to code the data.

Group

Exp_Con

1

96

1

127

1

127

1

119

1

109

1

143

1

1

1

106

1

109

2

114

2

88

2

104

2

104

2

91

2

96

2

2

2

114

2

132

From the above you can see that we used the “Group” variable to code for the two variables. The value of 1 was used to code for “LBW-Experimental”, while a value of 2 was used to code for “LBW-Control”. If you’re confused please study the table, above.

To generate the t-statistic,

  • Clik on [Statistics => Compare Means => Independent-Samples T Test] to launch the appropriate dialog box.
  • Select “exp_con” – the dependent variable list – and move it to the Test Variable(s): box.
  • Select “group” – the grouping variable list – and move it to the Grouping Variable: box.
  • The final step requires that the groups be defined. That is, one must specify that Group1 – the experimental group in this case – is coded as 1, and Group2 – the control group in this case – is coded as 2. To do this, click on the [Define Groups…] button. Click on the [Continue] button to return to the controlling dialog box.
  • Run the analysis by clicking on the [OK] button.

    The output for the current analysis extracted from the output window looks like the following.


The p-value of .004 is way lower than the cutoff of 0.025, and that suggests that the means are significantly different. Further, a Levene’s Test is performed to ensure that the correct results are used. In this case the variances are equal, however, the calculations for unequal variances are also presented, among some other statistics – some not presented.

In the next section we will briefly demonstrate the calculation of correlations and regression, as discussed in Chapter 9 of Howell. In truth, you should be able to work through many statistics with your current knowledge base and the help files, including correlations and regressions. Most statistics can be calculated with a few clicks of the mouse.

Correlations and Regression


This will be a brief tutorial, since there is very little that is required to calculate correlations and linear regressions. To calculate a simple correlation matrix, one must use [Statistics => Correlate => Bivariate…], and[Statistics => Regression => Linear] for the calculation of a linear regression.

For this section, the analyses presented in the computer section of the Correlation and Regression chapter will be replicated. To begin, enter the data as follows,

IQ

GPA

102

2.75

108

4.00

109

2.25

118

3.00

79

1.67

88

2.25

85

2.50

Simple Correlation

  • Click on [Statistics => Correlate => Bivariate…], then select and move “IQ” and “GPA” to the Variables: list. [Explore the options presented on this controlling dialog box.]
  • Click on [OK] to generate the requested statistics.

The results from output window should look like the following,


As you can see, r=0.702, and p=.000. The results suggest that the correlation is significant.

Note: In the above example we only created a correlation matrix based on two variables. The process of generating a matrix based on more than two variables is not different. That is, if the dataset consisted of 10 variables, they could have all been placed in the Variables: list. The resulting matrix would include all the possible pairwise correlations.

Correlation and Regression

Linear regression….it is possible to output the regression coefficients necessary to predict one variable from the other – that minimize error. To do so, one must select the [Statistics => Regression => Linear…] option. Further, there is a need to know which variable will be used as the dependent variable and which will be used as the independent variable(s). In our current example, GPA will be the dependent variable, and IQ will act as the independent variable. Specifically,

  • Initiate the procedure by clicking on [Statistics => Regression => Linear…]
  • Select and move GPA into the Dependent: variable box
  • Select andmove IQ into the Independent(s): variable box
  • Click on the [OK] to generate the statistics.

    Note: A variety of options can be accessed via the buttons on the bottom half of this controlling dialog box (e.g., Statistics, Plots,…). Many more statistics can be generated by explore the additional options via theStatistics button.

Some of the results of this analysis are presented below,


The correlation is still 0.702, and the p value is still 0.000. The additional statistics are “Constant”, or a from the text, and “Slope”, or B from the text. If you recall, the dependent variable is GPA, in this case. As such, one can predict GPA with the following,

GPA = -1.777 + 0.0448*IQ

The next section will discuss the calculation of the ANOVA.

One-Way ANOVA


As in the independent t-test datasheet, the data must be coded with a group variable. The data that will be used for the first part of this section is from Table 11.2, of Howell. There are 5 groups of 10 observations each – resulting in a total of 50 observations. The group variable will be coded from 1 to 5, for each group. Take a look at the following to get an idea of the coding.

Groups

Scores

1

9

1

8

1

6

1

7

2

7

2

9

2

6

5

10

5

19

5

11

The coding scheme uniquely identifies the origin of each observation.

To complete the analysis,

  • Select [Statistics => Compare Means => One-Way ANOVA…] to launch the controlling dialog box.
  • Select and move “Scores” into the Dependent list:
  • Select and move “Groups” into the Factor: list
  • Click on [OK]

    The preceeding is a complete spefication of the design for this oneway anova. The simple presentation of the results, as taken from the output window, will look like the following,


The analysis that was just performed provides minimal details with regard to the data. If you take a look at the controlling dialog box, you will find 3 additional buttons on the bottom half – [Contrasts…][Post Hoc..], and[Options…].


Selecting [Options…] you will find,


If Descriptive is enabled, then the descriptive statistics for each condition will be generated. Making Homogeneity-of-variance active forces a Levene’s test on the data. The statistics from both of these analyses will be reproduced in the output window.

Selecting [Post Hoc] will launch the following dialog box,


One can active one or multiple post hoc tests to be performed. The results will then be placed in the output window. For example, performing a R-E-G-W F statistic on the current data would produce the following,


Finally, one can use the [Contrasts…] option to specify linear and/or orthogonal sets of contrasts. One can also perform trend analysis via this option. For example, we may wish to contrast the third condition with the fifth,


For each contrast, the coefficients must be entered individually, and in order. Once can also enter multiple contrasts, by using the [Next] present in the dialog box. The result for the example contrast would look like the following,



Further, one can use the Polynomial option to test whether a specific trend in the data exists.

Factorial designs will be covered in the next section.

Factorial ANOVA


To conduct a Factorial ANOVA one only need extend the logic of the oneway design. Table 13.2 presents the data for a 2 by 5 factorial ANOVA. The first factor, AGE, has two levels, and the second factor, CONDITION, has five levels. So, once again each observation can be uniquely coded.

AGE

CONDITION

Old = 1

Counting = 1

Young = 2

Rhyming = 2

Adjective = 3

Imagery = 4

Intentional = 5

For each pairing of AGE and CONDITION, there are 10 observations. That is, 2*5 conditions by 10 observations per condition results in 100 observations, that can be coded as follows. [Note, that the names for the factors are meaniful.]

AGE

CONDITIO

Scores

1

1

9

1

1

8

1

1

6

1

1

1

7

1

2

7

1

2

9

1

2

6

1

1

1

1

5

10

1

5

19

1

1

5

11

2

1

8

2

1

6

2

1

4

2

2

1

7

2

2

10

2

2

7

2

2

8

2

2

2

2

5

21

2

5

19

2

2

5

21

Examine the table carefully, until you understand how the coding has been implemented. Note: one can enhance the readability of the output by using Value Labels for the two factors.


To compute the relevant statistics – a simple approach,

  • Select [Statistics => General Linear Model => Simple Factorial…]
  • Select and move “Scores” into the Dependent: box
  • Select and move “Age” into the Factor(s): box.
  • Click on [Define Range…] to specify the range of coding for the Age factor. Recall that 1 is used for Old and 2 is used for Young. So, the Minimum: value is <1>, and the Maximum: value is 2. Click on[Continue].
  • Select and move “Conditio” into the Dependent: box
  • Click on [Define Range…] to specify the range of the Condition factor. In this case the Minimum: value is 1 and the Maximum: value is 5.

    By clicking on the [Options…] button one has the opportunity to select the Method used. According to the online help,

    Method: Allows you to choose an alternate method for decomposing sums of squares. Method selection controls how the effects are assessed.”

    For the our purposes, selecting the Hierarchical, or the Experimental method will make available the option to output Means and counts. — Note: I don’t know the details of these methods, however, they are probably documented.

  • Under [Options…] activate Hierarchical, or Experimental, then activate Means and counts – Click [Continue]
  • Click on [OK] to generate the output.


    As you can see the use of the Means and count option produces a nice summary table, with all the Variable Labels and Value Labels that were incorporated into the datasheet. Again, the use of those options makes the output a great deal more readable.


    The output is a complete source table with the factors identified with Variable Labels

As noted earlier, the analysis that was just conducted is the simplest approach to performing a Factorial ANOVA. If one uses [Statistics => General Linear Model => GLM – General Factorial…], then more options become available. The specification of the Dependent and Independent factors is the as the method used for the Simple Factorial analysis. Beyond that, the options include,

  • By selecting [Model…], one can specify a Custom model. The default is for a Fully Factorial model, however, with the Custom option one can explicitly determine the effects to look at.
  • The Contasts option allows one “test the differences among the levels of a factor” (see the manual for greater detail).
  • Various graphs can be specified with the [Plots…] option. For example, one can plot “Conditio” on the Horizontal Axis:, and “Age” on Separate Lines:, to generate a simple “conditio*age” plot (see the dialog box for [Plots…],


  • The standard post-hoc tests for each factor can be calculated by selecting the desired options under [Post Hoc…]. All one has to do is select the factors to analyze and the appropriate post-hoc(s).
  • The [Options…] dialog box provides a number of diagnostic and descriptive features. One can generate descriptive statistics, estimates of effect size, and tests for homogeneity of variance – among others. An example source table using some of these options would look like the following,


The use of the GLM – General Factorial procedure offers a great deal more than the Simple Factorial. Depending on your needs, the former procedure may provide greater insight into your data. Explore these options!

Higher order factorial designs are carried in the same manner as the two factor analysis presented above. One need only code the factors appropriately, and enter the corresponding observations.

source : www.psych.utoronto.ca

The Future Of Indonesia

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Though Indonesia was recently welcomed into the G20 and has earned lower middle income status by the World Bank, it faces significant development challenges which need to be addressed for the country to sustainably thrive in the future. It is still economically fragile after the Asian financial crisis and has mixed progress toward achieving the Millennium Development Goals (MDG‟s). The recently decentralized government is faced with increased pressure to ensure fair resource distribution among districts and regions in an innovative, sustainable fashion that doesn‟t further strip the fragile environment of its resources for economic gain. This will be especially critical for 69% of the population who will be working age in the next few decades,1 who will require education, health and security to support their quality of life and the country‟s economic growth. The Government of Indonesia adopted a Medium Term Development Plan (RPJMN) 2010-2014, “Development for All‟,2 which seeks to raise levels of economic growth, create jobs and accelerate achievement of the MDG‟s. Meeting these stated goals in the delicate moment of democracy consolidation and economic recovery will require a comprehensive package of aggressive (but reasonable) policy reforms.

This paper provides an account of Indonesia‟s recent history to unveil the factors shaping its development progress and highlights its environmental damage, deforestation specifically, as one of the major issues facing the country today. Other critical development challenges include urbanization and a growing population, dependence on primary commodity exports, inequalities in health and education, expensive and fragile infrastructure, and the need to create democratic governance mechanisms within a historically corrupt system. I have used an integrated computer simulation of global change, International Futures (IFs), to aid in the forecast of fuel subsidy reduction and reforestation initiatives through the year 2030. Though the IFs program has a high level of uncertainty in forecasting the outcome of policies, it can be used by policymakers to imagine alternative futures and the feasibility of making change. The results show that, if implemented properly, Indonesia can achieve its national goals while compensating for its historically destructive environmental practices. This will aid in further economic growth by promoting a favorable climate for foreign investment and support while ensuring sustainability for future generations of Indonesians.

1. Introduction

Indonesia‟s national motto of “unity in diversity‟ is a central theme running through all of the country‟s development trends. The archipelago consists of 17,000 islands occupied by 242 million people, giving it the rank of the fourth most populous country in the world.3 Its global positioning has led to strong influences from China, the Middle East and Europe, causing significant religious and ethnic heterogeneity evidenced by its divisions into 300 distinct ethno linguistic groups.4 The diverse population is dispersed in a “core-periphery‟ model whereby the majority of the population lives and continues to migrate to the urban cores. The country has significant natural resources, including timber, fish, petroleum, natural gas and a variety of minerals, and one of the most diverse terrestrial and marine ecosystems in the world.

In the face of its geographic fragmentation and demographic and biological diversity, Indonesia has succeeded in achieving relative economic stability since its independence from strong central control and a rigid hierarchical system of Dutch governance in 1945. Quickly following independence the first President Sukarno enacted laws establishing authority and government structure at a more local level to give greater discretion to regional authorities. However, starting in 1959 Sukarno led Indonesia into a more authoritarian period under his “Guided Democracy‟, a Presidential Decree in which the state became obsessed with national unity, promoting economic development through socialist policies and remaining outside of the world market. Conditions worsened during this period, hitting a low in 1965 with an attempted coup followed by social upheavals against the Communist Party.5 This gave birth to the “New Order‟, a three decade period of highly centralized governance led by President Suharto, marked by rapid growth and reduction in inflation leading to increased foreign aid and investment. Suharto resigned in May 1998 as a response to increased social unrest following the Asian financial crisis, making way for the institution of a democratic political system.

The rapid decentralization process that followed Suharto‟s downfall devolved authority to all 30 Indonesian provinces to manage their own administration, public welfare and public health sectors through unique models of government structure aligning with local custom.6 (See the “Big Bang Decentralization‟ section for a more complete account of the decentralization history and framework.) In the face of this transition, the newly elected officials have dealt with various crises, including the aftermath of the Asian financial crisis, multiple natural disasters such as the 2004 earthquake and tsunami which killed 160,000 people and destroyed the homes of 680,000,7 the recent global economic crisis, from which the country is still recovering, and ethnic strife remaining from the oppressive regime of the past. Simultaneously, Indonesia is feeling increased external pressure to remedy the destruction on the natural environment caused by 30 years of export led growth. It is in this highly transitional context that we can explore Indonesia‟s development trends in order to better understand the challenges it faces today.

The majority of this population seeks employment in the urban centers, aligning with historical internal migration patterns and explaining the population growth rate differential in urban areas as compared to rural regions. In 1960, 14.6 percent of the population resided in urban areas, but by 2005 the urban population was up to 48 percent. For the first time in its history, the population in urban areas exceeds that of rural. If current trends continue, the IFs model shows that by 2030 nearly 60% of the population will live in urban centers. The country is faced with the challenge of accommodating dense populations in urban settings such as Jakarta, which has grown from 0.5 million people in the 1930‟s to 20 million in 1995, holding 10% of the national population.13

As a response, the Indonesian government has historically intervened in migration patterns to achieve a closer match between population densities and natural resources. Such an example is the transmigration program, the largest agricultural migration program of its kind in the world, which seeks to shift people from the densely populated core to outlying islands in the island chain.14 This program has devastating impacts on the environment that need to be reconciled, caused by increased deforestation as dwellings and infrastructure are installed to serve these migrant communities. The increased autonomy granted to outlying regional governments under decentralization has the potential to empower districts to engage in sustainable development practices and provide employment and incentives for people to stay in their villages rather than moving to the cities. This, however, is contingent on sufficient economic resources for these regions.

2. Prospects for the Future

The most recent World Bank economic report on Indonesia shows that the country continues to recover from the global economic crisis, achieving growth above pre-crisis levels. Though the GDP per capita has been steadily increasing, the number of Indonesians who have enjoyed this economic success is questionable. Government investment in the public sector fell from 7% in 1996 to only 4% in 2000; health spending has fallen below 3% of GDP, education expenditures only amount to 6% of the budget and infrastructure only 2%. Additionally, as the IFs model shows, Indonesia‟s Gini value in 2000 was .303 and by 2005 it rose to a record high level of .394. The IFs model forecasts that it will remain just below this level through 2030.

More than half of the population lives on less than $2/day and remains vulnerable to internal and external shocks at all levels, including natural disasters, susceptibility to illness and government restructuring. Decentralization poses additional social and economic obstacles to poverty alleviation and more equal economic distribution as local governments scramble to expand service delivery to their populations. Social services could be further weakened unless significant efforts are made to alleviate corruption by local leaders who are vying for more power without accountability. Though government efforts have been made to fix some of the inefficiencies in decentralization legislation, such as reforms to Laws 22 and 25 enacted in 2004 to increase the role of higher government levels to facilitate more effective budgetary management and administration, only time will tell if the granting of local autonomy will create a healthy environment for democratic development or further fractionalize the country.

The government‟s history of legitimizing itself through economic growth without due regard for the environment will have drastic effects on the stock of key natural resources, a significant threat to health and human welfare caused by industrial and urban pollution and increased conflicts over the use of resources. Future growth and development will depend on the existence of natural resources and the sustainability of critical ecosystems. The problems associated with rapid industrial sector growth concentrated in urban areas will ultimately lead to resistance of industrial expansion and have profound effects on the overall economy.

2.1. Medium Term Development Plan (RPJMN)

The government‟s Medium Term Development Plan 2010-2014 may prove to be an effective catalyst to enact the necessary environmental improvements and ensure the poor do not suffer through this process if policy reforms are appropriately implemented and monitored. President Yudhoyono and Vice President Boediono formulated the most recent Medium Term Development Plan (RPJMN) as part of a longer development initiative (RPJPN 2005-2025) to realize an Indonesia that is prosperous, democratic and just through focusing on improvement of 11 development priorities, a few of which are outlined below:

  • Average economic growth of 6.3-6.8% per annum; economic growth more than 7% before 2014
  • Poverty rate of 8-10% by 2014
  • Population growth of 1.1% by 2014
  • Illiteracy rate of population aged less than 15 years reduced to 4.18% in 2014
  • Life expectancy increase to 72 years in 2014
  • Mortality rate per 1,000 births reduced to 24 by 2014
  • HIV prevalence less than 0.5% by 2014
  • Corruption perception Index 5.0 in 2014

The government plans to achieve these stated goals through a combination of initiatives funded through the public sector (18%) and private sector (82%). The above chosen development and sectoral targets included in the RPJMN can be measured in the IFs program to determine the effectiveness of policy interventions in meeting national priorities.

2.2 Policy Recommendations

Any long-term environmental policy reform would need to set up a regulatory and economic framework which provides incentives to change behavior, accounts for environmental costs, enhances resource conservation and improves revenue collection mechanisms. One example of this is to reduce fuel subsidies while providing conditional and unconditional cash transfers to the poor – compensating for short term economic burden while increasing access to education and health. Simultaneously, a carefully implemented reforestation initiative which protects sufficient land for crop production would serve to protect biodiversity and offset increased carbon emissions. Good governance is critical during this process to manage the distribution of funding to poor households and create reforestation monitoring mechanisms to avoid illegal logging and mining activities.

2.2.1 Subsidy Removal and Cash Transfer Program

The removal of fuel subsidies is an important step in the direction of internalizing the costs of environmental destruction into production, re-pricing good to align with international benchmarks and making producers and consumers accountable for unsustainable practices. The increases in world fuel prices in 2005 inspired such a policy, whereby the government significantly decreased subsidies and increased fuel prices by 29% and again later that year by114%. Though this created significant funding pools, up to $10 billion in 2006, it further marginalized the poor who were unable to meet the increased fuel costs. The government implemented an Unconditional Cash Transfer (UCT) program in August 2005 to ensure the impoverished population would not suffer. There were inherent problems with the

unconditional nature of this initiative, mainly that a large portion of the recipients were not classified as poor by government standards. The Conditional Cash Transfer Program (CCT), enacted in 2007, connected payments to education and health spending to eliminate some of the targeting problems of the UCT program. This pilot CCT program applied cash transfers to both households (individuals receive quarterly payments through the post office as long as they meet requirements of using specified health and education services) and communities (communities decide how to best use allocated block grants to achieve health and education targets).

Since 1998 the Indonesian government implemented the Kecamatan Development Program (KDP) and the Urban Poverty Project (UPP), large scale community development programs implementing participatory, community driven development. In August 2006 President Yudhoyono announced a dual-component poverty alleviation program consisting of the National Community Empowerment Program (PNPM-Mandiri), building upon the KDP and UPP which ended in 2005, and the CCT program, which together targeted all 70,000 villages in 5,300 rural and urban sub-districts in the country.The cash transfer program, implemented in six provinces, is designed to achieve objectives and goals in line with the national development plan and the MDG‟s. More specifically, these programs target poverty reduction, maternal mortality reduction, child mortality reduction and ensure universal coverage of basic education. The CCT emphasizes certain lagging health and education outcomes through targeted community investments. It is an appropriate policy intervention for Indonesia for multiple reasons: it utilizes mechanisms developed through eight years of community driven development; allows communities to articulate service demands and propose local solutions; and utilizes a participatory approach to better target services to self-identified beneficiaries. Though the Conditional Cash Transfer program is in a pilot stage and is thus limited in scope, the likelihood of the program being implemented on a national scale is very high, suggesting many potential benefits not only for the impoverished but for the country as a whole.

2.2.2 Reforestation Initiative

A reforestation initiative would expand and protect biodiversity, improve human health, mitigate the alarmingly high level of the country‟s greenhouse gas emissions and provide indigenous populations an opportunity to reclaim their livelihoods. See Appendix 1 for the drivers and forward linkages of environmental change.The Suharto government created a national forest Reforestation Fund in 1989 to support reforestation and rehabilitation of degraded land. However, during this time the Ministry of Forestry used the fund to promote the development of industrial timber and pulpwood plantations and granted contracts to plantation companies with close ties to political elites. A subsequent audit of the Fund showed losses of $5.2 billion in public funds during a five year period in the mid 1990‟s alone.

Since then, the government has taken steps to restore legitimacy to the Fund, but the challenges of financial management and administration posed by decentralization remain. The likelihood of adherence to a wide scale reforestation effort today is high, considering the government‟s interest in participating in a Reducing Emissions from Deforestation and Forest Degradation (REDD) program, a global effort which uses market incentives to reduce greenhouse emissions from deforestation. This type of international forest carbon market is expected to be established after 2012 and could provide tremendous financial opportunities for Indonesia. Estimates of potential gains to the country through REDD range from $0.5-$2 billion/year. As of this year, the government has planned on a two-year moratorium on new forestry concession on rainforest lands and peat swamps and will be supported over the next five years by a $1 billion contribution from Norway. Future external contributions and funding set aside from the domestic budget could finance the reforestation efforts in the future.

Along with these initiatives to protect environmental biodiversity through reforestation and promote environmental accountability through fuel subsidy removal, action must be taken to improve governance to curb destructive practices and ensure fair distribution of funding to the poor. Integrating these proposed policy reforms into the IFs model, we can forecast Indonesia‟s future development path through year 2030 to determine if these interventions will catalyze the achievement of the country‟s development goals and the broader MDG‟s.

3. The Intervention

In order to mimic a nationwide Conditional Cash Transfer program, I first increased the value of government transfers to unskilled households (govhhtrnwelm) to 1.2 starting in 2010 through 2030. Though this would transfer government funding to households, it does not subsequently tie the increased household income on education or health expenditures as the program requires. Rather, IFs automatically assumes the additional income will be spent on domestic consumption. To create a scenario more realistically tied to the CCT program, I increased the total transition rate of students into lower secondary education programs (edseclowtrangr) to 1.0 and lowered infant mortality (hlmininfmort) to 1.0 through 2030. I manipulated the level of corruption as a fourth intervention point, aligning with the national anti-corruption efforts already in place. To do this, I increased the government corruption multiplier (govcorruptm) starting in 2010 by 250%, forcing Indonesia to reach 6.69 on Transparency International‟s

Corruption Perception Index by 2030.

The main drivers for environmental change are population, land use, economic activities and governance. Within the environmental leverage points, IFs provides forest land use as the indicator most relevant to the reforestation initiative. In order to be fully accurate, the model would need to differentiate between the types of forests generated (to account for such differences such as a primal forest or timber plantation). However, I have assumed that the land area will not be reforested for future clearing. Although ecological activity and population are highly correlated, there would likely be no effect in lowering TFR on the amount of forest land given that the land is not automatically credited to nature. Neither economy nor governance result in direct changes for environmental indictors in the model, thus the one possible intervention that will effect change is the Forest Protection Multiplier, forestm, which causes the area dedicated to forest land use to change. Since forestm displaces other land use and thus would have grave implications on agricultural production and food security, I implemented a moderate increase to 1.1 starting in 2010 through the year 2030 and after that it returns to the neutral value of 1.0.

The scenario implemented as would have an inherent conflict between improving the natural environment and food security. To modify the intervention to increase the likelihood of its implementation, I increased the agricultural yields multiplier (ylm) by 1.2 through 2030, after which time it was decreased back to 1.0.

4. Policy Challenges

The ultimate goal of implementing this package of reforms is to reverse the devastation on the environment caused by decades of stripping the land of its natural resources for short-term economic gain. As Indonesia has made the shift from an agricultural to a manufacturing economy, thus diversifying its income, it has the opportunity to effectuate positive environmental changes. However, implementing these policies will face challenges from those who are unable and unwilling to financially absorb the shocks caused by subsidy reductions and the decline in agricultural land. Monitoring mechanisms need to be put into place to protect the reforested areas from illegal logging, which has received recent global attention as a critical problem in the country. The corrupt governance system allowing for such practices needs to be further cleaned if progress is to be made in adhering to existing environmental law and bringing transparency to governance.

Both the community and household CCT face additional challenges in ensuring equitable access to services. Supply shortages, both in medical supplies and junior secondary schools in particular, quality of services due to increased beneficiaries, and the extra burden of administration and management imposed on newly formed regional governments are serious threats to the effectiveness of the CCT programs. The marked improvements in education and health as a result of the CCT program and anti-corruption efforts places extra pressure on the government to provide quality employment for a growing population of educated citizens entering the labor force. Currently, over 40% of 15-24 year olds with completed senior secondary school in the labor market are unemployed, partly due to lack of information about employer expectations but largely due to growing employment demand without a correlating supply. Regional governments and the private sector should collaborate to ensure youth exiting the education system have the requisite skills to successfully gain and retain employment.

The reforestation effort faces land tenure and access issues related to the rights of communities and the role of private enterprises. After decentralization, the relationship between the sectoral ministries and the regional authorities are more collaborative than top-down as the communities recognize their increased power and leverage they have to have their voices heard. If the central government wants to continue to curb conflict, the rights of the traditional peoples demanding a community-based approach to natural resource management must be respected. The unique adoptive management and land tending models of these communities makes formulation of general policies nearly impossible. The central ministries need to play an active role in evaluating the lessons learned from the province-based service provision models in other recently decentralized countries in the region, providing resources to provinces to effectively train and manage the social and environmental service workforce and change its role in relationship to regional governments.

In looking to the future, Indonesia must focus its attention away from environmentally destructive practices for economic gain. Given the fragile nature of the state post economic crisis and the increasing global prices of oil, which is heavily consumed by the industrializing nation with a growing consumer population, the inclination to expand cash crops such as palm oil and engage in strip mining for increased coal use will be high. However, the country must focus on enhancing existing and integrating new technology into the agricultural and services sectors to make production more efficient as well as continuing to diversify its economy through the transition into manufacturing. Tapping in to its huge stock of geothermal resources as a source of renewable energy is a viable option to transition away from the use of fossil fuels. Positioned on the ring of fire, the country holds 40% of the world‟s potential geothermal resources.

5. Conclusion

Providing a careful historical analysis of the factors that shape a country‟s growth path is the first step to understanding its future trajectory and aids in informing policy and action. Though it is framed on uncertainty, the IFs model provides detail to general understanding of growth trends and offers a glimmer of hope for the future. Given its limitations, the model shows that an approach to reverse the environmental damage to Indonesia while protecting the livelihoods of the population is possible. It also presents a realistic challenge to policy implementation, whereby following one goal has negative spillover effects on other sectors and parts of the global system. It is ultimately up to the policymaker and the population he/she represents to decide which goal to pursue, based on feasibility of implementation and social values.

This paper covered the major development issues chosen by the author and in no way provides comprehensive coverage of all of the challenges the country faces. In reality, the Indonesian government and various ministries are working to tackle a complex array of development challenges to meet the holistic needs of its population and respond to external pressures. The government is continuing to engage in diverse activities that will continue domestic growth and expand its partnerships with external agencies to garner support in its effort to achieve its development goals. Such collaborative efforts offer opportunities for Indonesia‟s growth through an influx of funding for capacity building and technical assistance projects. The government has a real opportunity to reverse environmental damage, reduce poverty and grow the economy if it continues to pursue necessary policy reforms with support from its population and collaborative partners.


J e s s i e G o f f

N o v e m b e r 1 9 , 2 0 1 0

I N T S 4 6 0 1 : D e v e l o p m e n t
F o r e c a s t i n g J o s e f K o r b e l S c h o o l o f
I n t e r n a t i o n a l S t u d i e

  1. International Futures, version 6.36 (2010)
  1. United Nations 5
  1. United Nations. United Nations Partnership for Development Framework 2011-2015 Indonesia (2010. Print) 2
  1. Hugo, Graeme, et al. The Demographic Dimension in Indonesian Development (Singapore: Oxford University Press, 1987. Print) 11
    1. Dick, Howard, et al. The Emergence of a National Economy: An Economic History of Indonesia 1800-2000

    (Australia: Allen and Unwin, 2002. Print) 26

Epistemologi Friedrich Wilhelm Nietzsche

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A. Pendahuluan

Ada satu pertanyaan yang begitu penting untuk diajukan, yaitu : Apakah Nietzsche mempunyai konsep epistemologi. Ini pertanyaan yang muncul dalam pikiran kita pada umumnya, atau bahkan bagi mereka yang berkutat di dunia filsafat. Memang, Nietzsche menjadi terkenal bukan karena pandangan epistemologinya. Ia lebih di kenal karena pemikirannya dalam bidang filsafat moral atau etika. Pemikiran epistemologinya tidak begitu diminati oleh para epistemolog. Tetapi disinilah Nietzsche mengajukan pandangan kontroversialnya. Pandangan epistemologinya diawali dengan suatu asumsi dasar bahwa kita harus menggunakan skeptisme radikal terhadap kemampuan akal. Tidak ada yang dapat dipercaya dari akal. Terlalu naïf jika akal dipercaya mampu memperoleh kebenaran. Jika orang beranggapan dengan akal diperoleh pengetahuan atau kebenaran, maka akal sekaligus merupakan sumber kekeliruan.

Epistemologi Nietzsche di tengah zaman modern yang ditandai dengan dominasi akal ini tampak aneh dan sulit untuk diterima. Pendobrakan dogmatism (kemapanan) akal dengan konsep The Will to Power (kehendak untuk berkuasa), membuat Nietzsche seperti dalang yang keluar dari pakem. Perbedaan itu sangat tampak sekali dan bahkan berkontradiksi 180 derajat antara filsafat Nietzsche dengan pemikir-pemikir besar yang menjadi kekuatan mainstream saat itu, baik dalam penggunaan bahasa epistemologi maupun materi yang disajikan. Terlepas dari semua itu, epistemologi Nietzsche layak untuk dikaji dan diperbincangkan. Pemikirannya yang tidak bisa diterima oleh zamannya mulai menunjukkan pengaruh dan kekuatannya pada masa sekarang ini. Hal ini dapat dirasakan pada epistemologi Karl Popper dengan falsifikasinya dan juga pada pemikiran kaum eksistensialis. Nuansa Nietzschean dalam epistemologi postmodernisme (pluralism, dekonstruksi, relativitas) sangat terasa sekali.

B. Profil Nietzsche

Friedrich Wilhelm Nietzsche (lahir di Röcken dekat Lützen15 Oktober 1844 – meninggal di Weimar25 Agustus 1900 pada umur 55 tahun) adalah seorang filsuf Jerman dan seorang ahli ilmu filologi yang meneliti teks-teks kuno. Ia merupakan salah seorang tokoh pertama dari eksistensialisme modern yang ateis. Nietzsche dilahirkan di Kota Rocken di wilayah Sachsen. Orang tuanya adalah pendeta Luther Carl Ludwig Nietzsche (1813-1849) dan istrinya Franziska, dengan nama lajang Oehler (1826-1897). Ia diberi nama untuk menghormati Kaisar Prusia Friedrich Wilhelm IV yang memiliki tanggal lahir yang sama. Adik perempuannya Elisabeth dilahirkan pada 1846. Setelah kematian ayahnya pada 1849 dan adiknya Ludwig Joseph (1848-1859), keluarga ini pindah ke Naumburg dekat Saale.


Filsafat Nietzsche adalah filsafat yang memandang kebenaran atau dikenal dengan filsafat perspektivisme. Ia mengkritik kebudayaan Barat pada zamannya (Umwertung aller Werten) yang sebagian besar dipengaruhi oleh pemikiran Plato dan tradisi kekristenan (keduanya mengacu kepada paradigm kehidupan setelah kematian). Nietzsche juga dikenal sebagai filsuf seniman dan banyak mengilhami pelukis modern Eropa di awal abad ke-20, seperti Franz Marc, Francis Bacon dan Giorgio de Chirico, juga para penulis seperti Robert Musil dan Thomas Mann. Menurut Nietzsche kegiatan seni adalah kegiatan metafisik yang memiliki kemampuan untuk mentransformasikan tragedi hidup.

Filsafat Nietzsche tidak bisa dipisahkan dari kehidupannya. Filsafatnya adalah pandangan hidupnya. Ada nilai lebih membaca karya Nietzsche yang tidak hanya sekedar memberikan pengetahuan tentang filsafat, namun lebih jauh dari itu, yakni pengetahuan tentang hidup. Ia mempunyai arti penting dalam sejarah filsafat. Nilai historis Nietzsche sangat besar. Pemikirannya yang meloncat dan meramalkan masa depan sangatlah mengagumkan. Ia adalah seorang filsuf bagi para filsuf, tetapi ia lebih besar dari para filsuf lainnya, karena ia juga menjadi filsuf bagi orang kebanyakan (Hollingdale, 1968:10-11). Filsafat Nietzsche seperti samudra yang menampung air dari berbagai aliran sungai. Ada warna realism, empirisme, skeptime, radikalisme, positivism, vitalisme dan pragmatism. Dari berbagai warna aliran tersebut di tangan Nietzsche melebur menjadi filsafat nihilism, dimana warna berbagai aliran tersebut sulit untuk dilihat wujudnya secara terpisah.

C. Karakteristik Epistemologi Nietzsche

Mempelajari epistemology Nietzsche tanpa menelaah keseluruhan filsafatnya seperti mengambil mozaik terpisah dari keseluruhannya, sehingga akan tampak aneh dan tidak bermakna. Ia tidak membahas epistemologi sebagai cabang filsafat tersendiri sebagaimana filsuf-filsuf lainnya. Epistemologi merupakan sebagian kecil dari konsep The Will to Power. Pada tulisan ini akan membahas masalah pokok yang mendasari corak epistemologi Nietzsche.

  • Landasan Ontologi

Ontologi merupakan sebuah konsep dasar yang menopang suatu sistem filsafat. Dalam bidang ontologi Nietzsche menolak terminologi Immanuel Kant yang melihat kenyataan dalam dua dikotomi Nomena dan Fenomena. Fenomena hanyalah sekedar gejala yang tampak di depan subjek. Ia bukanlah kenyataan. Kenyataan yang sebenarnya ada dibalik fenomena. Kenyataan sejati merupakan Das Ding An Sich (hal itu sendiri) ada di balik bendanya. Nomenalah yang hakiki.

Dalam terminologi Nietzsche, dikotomi semacam ini tidak berlaku, baginya, kenyataan itu adalah apa yang nyata yang dapat ditangkap subjek. Objek atau benda itulah kenyataannya. Inilah kenyataan sejati yang tidak dapat disangkal adanya. Tidak ada sesuatu di balik bendanya. Das Ding An Sich hanyalah lelucon sebagai suatu ajaran yang masih dikuasai oleh dogma. Sebagaimana dipercaya akal manusia tidak akan mampu mengetahui nomena. Sesuatu yang tidak dapat ditangkap, diketahui dan hanya bisa diandaikan adanya yang tidak layak untuk dipercaya. Kenyataan adalah apa yang ada di dunia ini, yang nyata, faktual, yang dapat ditangkap subjek. Ajaran Das Ding An Sich ini menempatkan dan membuat hidup manusia menjadi kurang bermakna. Dunia yang adanya nun jauh disana (yang hanya diandaikan bukan fakta) lebih dihargai.

Konsep ontologi Nietzsche ini mempunyai implikasi dalam ajaran tentang manusia. Manusia untuk menjadi manusia menghadirkan diri lewat budaya. Pandangan tentang manusia dapat dikatakan cenderung ke monisme, dimana hakikat manusia itu adalah tubuhnya. Yang dipandang manusia itu adalah yang bereksistensi, sedangkan eksistensi itu terjadi jika ada tubuh. Hal ini sangat jelas diungkapkan Zarathustra :

Aku adalah tubuh dan “jiwa” demikian dikatakan sang anak. Apa salahnya berbicara seperti seorang anak?

Tapi mereka telah bangun, dan mereka yang tahu berkata : “aku adalah tubuh seluruhnya. Tidak ada yang lain, jiwa adalah sesuatu dari tubuh” (Nietzsche, 1969: 146)

Tubuh adalah sebuah akal besar, kemajemukan yang bermakna satu, perang dan damai, kawanan domba sekaligus gembalanya.

“Akal kecilmu adalah alat dari tubuhmu itu, saudaraku, yang kau sebut “ruh” itu adalah alat dari tubuh. Sebuah alat dan mainan kecil dari akal besar”.

Dari pandangan yang berat sebelah dengan dominasi tubuh atas jiwa semacam ini, tidak mengherankan jika ia memberi perhatian dan penghargaan pada ilmu biologi.

  • The Will to Power sebagai Titik Pusat Ajarannya

Karya Der Wille zur Macht (The will to power) merupakan magnum opus Nieetzsche. Inti semua ajarannya terdapat disini. Segala konsep dan masalah yang diperbncangkan selalu bermuara pada kehendak untuk berkuasa. Sebagai mana diungkapkan oleh Walter Kaufmann :

 Konsepsi kehendak untuk berkuasa adalah titik pusat dari filsafat Nietzsche. Dalam buku Aporishma-nya, ia menemukan kehendak untuk berkuasa, berkarya dalam segala tingkah laku dan penilaian manusia. Dalam Zarathustra, ia mengungkapkan bahwa kehendak untuk berkuasa merupakan motif dasar dan mengatakan bahwa kehendak itu terdapat pada semua makhluk hidup. (Dalam karyanya kemudian ia menganggapnya telah menembus sampai pada kehendak tak hidup) (Kaufmann, 1967: 510)

Pengetahuan sebagai salah satu dari sekian banyak kegiatan manusia tentu saja tidak dapat dilepaskan dari konsep ini. Nietzsche melihat pengetahuan itu dalam kerangka yang lebih luas dan menyeluruh dalam rangka memahami manusia secara utuh. Ia memasukkan unsur yang tidak dibahas dengan pemikiran epistemologi sebelumnya, yaitu unsur motif kegiatan mengetahui. Menghubungkan kehendak untuk berkuasa dengan pengetahuan merupakan hal yang aneh apabila dibahas dalam kerangka pengetahuan (epistemologi) manusia secara sempit.

Konsepnya akan tampak jelas jika dipahami dalam kerangka kegiatan (pengetahuan) manusia yang lebih luas. Justru ia melangkah lebih jauh dari para pendahulunya, dimana ia sudah menginjakkan kaki pada wilayah yang sekarang ini disebut sebagai Filsafat Ilmu yang pada masa itu belum mendapatkan perhatian. Inilah yang merupakan ciri dari pemikiran Nietzsche, dimana pemikirannya selalu mendahului satu atau dua tingkat pada sesudahnya. Epistemologinya jelas sekali merupakan kritik terhadap epistemologi tradisional, epistemologi sempit.

  • Vitalisme dan Nihilisme

Siapapun tidak menyangkal bahwa Nietzsche adalah seorang vitalis. Namun, vitalismenya berbeda dengan vitalisme Henry Bergson dimana elan vital dipahami sebagai daya hidup, unsur yang merupakan inti hidup. Vitalisme pada Nietzsche lebih bersifat aktif. Vitalisme dalam pengertian ini mengandung makna semangat hidup. Hidup itu sangat berharga. Kecintaan yang luar biasa terhadap hidup bukan berarti takut untuk mati. Hidup harus dihadapi dengan penuh keberanian, tidak boleh menyerah. Manusia harus berani berkata ya untuk setiap tantangan dan bahaya. Dari tantangan dan bahaya inilah manusia akan menjadi besar.

Manusia itu agung asal mau menjulangkan semangat hidup dan gairahnya setinggi-tingginya. Untuk itu, manusia harus bebas dari kekuatiran akan dosa dan bebas dari nilai-nilai tradisional yang membelenggu potensi kemanusiaannya. Cinta kehidupan berarti harus sanggup menangggung kenyataan bahwa manusia bukanlah sesuatu yang sudah selesai, ia selalu dalam proses menjadi. Manusia adalah jembatan antara binatang dan manusia agung. Ke manapun ia menoleh, ia akan menatap ancaman dan bahaya (Fuad Hasan, 1989: 62).

Aktivitas pemikiran harus diletakkan pada landasan keberanian, yang berasal dari keinginan untuk terus maju dan menantang penghalang. Manusia bebas itu harus terus berkreasi, mencipta.Dalam berkreasi ini harus menelorkan hal-hal yang benar-benar baru, orisinal, walalupun harus bertentangan dengan pemikiran pada masa itu. Di sinilah Nietzsche sampai pada Nihilisme. Nihilisme merupakan syarat untuk menjamin orisinalitas dalam berkreasi sehungga kreasi itu benar-benar bermakna. Orang harus berani menolak nilai-nilai dan pemikiran yang ada sebelumnya. Teori-teori, hukum-hukum, pengetahuan yang diciptakan harus benar-benar dilepaskan dari konsep sebelumnya. Teori-teori yang muncuil tidak akan bermakna jika hanya mengukuhkan atau mengukur teori yang sudah ada. Bahkan, teori yang sudah besar dan mapan pun harus dilepaskan.

Kritik dan penolakan terhadapa epistemologi tradisional yang berusaha memperoleh kebenaran bukan semata-mata karena semangat nihilismenya. Selama teori yang ada sebelumnya selalu dianggap benar, maka tidak akan muncul pengetahuan yang baru. Dengan sendirinya tidak akan ada kemajuan. Di sinilah Nietzsche mengajarkan suatu keterbukaan ilmu yang pada abad ke-20 ini diteruskan oleh Karl R. Popper.

D. Epistemologi Martil Nietzsche
  • Perang Melawan Kemapanan Akal

Akal dalam bahasa diibaratkan sekedar sebagai seorang tua yang dungu.

Saya kuatir tidak bisa melepaskan diri dari Tuhan hanya karena tata bahasa (Nietzsche, 1968:35).

……Tetapi telah lama saya menyatakan perang terhadap optimisme kemampuan akan (Nietzsche, 1968:535).

Roh, sesuatu yang berpikir, yang mungkin walaupun absolut. Roh murni konsepsi ini merupakan turunan kedua dari introspeksi palsu yang mempercayai tindakan berpikir: Pertama sebuah tindakan yang tidak terjadi dibayangkan “berpikir” dan Kedua subjek substratum di mana setiap tindakan berpikir dan bukan tindakan lain memiliki asal-usulnya baik perbuatan maupun pelaku yang merupakan fiksi (Nietzsche, 1968: 477).

  • Problem Kebenaran

Kebenaran adalah semacam kesalahan , dimana tanpa kebenaran spesies makhluk hidup tentu tidak dapat hidup (Nietzsche, 1968: 493).

“Konsep Kebenaran” adalah sesuatu yang tidak bermakna. Seluruh wilayah ‘benar salahnya’ hanya digunakan untuk hubungan-hubungan, bukan ‘pada dirinya sendiri’. Tidak ada ‘esensi pada dirinya’ (yang membentuk esensi hanyalah hubungan-hubungan), demikian juga tidak ada pengetahuan pada dirinya sendiri.

Aporishma 533 :

Kebenaran dari sudut pandang perasaan adalah sesuatu yang secara kuat menggugah perasaan (ego).

 Dari sudut pandang pikiran , kebenaran adalah sesuatu yang memberikan perasaan paling agung akan kekuatan.

 Dari sudut sentuhan, penglihatan dan pendengaran kebenaran adalah sesuatu yang mengandung resistensi paling besar (Nietzsche, 1968: 533)

 Kebenaran menurut cara berpikir saya tidak haru mengacu pada antitesis kekeliruan, tetapi dalam hal-hal yang paling mendasar hanyalah merupakan hubungan antara berbagai macam kekeliruan. Mungkin kekeliruan yang satu dianggap lebih tua, lebih mendalam dari yang lain, bahkan tidak dapat diganggu gugat lagi seperti halnya suatu entitas dari spesies kita, yang tidak dapat hidup tanpanya. Sementara itu kekeliruan lain tidak memaksa kita untuk menjadikannya sebagai syarat hidup, tetapi jika dibandingkan dengan tiran-tiran seperti ini pasti akan tersisih dan ditolak (Nietzsche, 1968: 535).

  •  Keputuasan Benar-Salah

Baiklah! Tetapi jika aku belum “mengetahui” apakah ada pengetahuan atau mungkinkah ada pengetahuan, aku tidak dapat mengajukan pertanyaan secara beralasan “apa itu pengetahuan?”. Sebagaimana diyakini Kant dalam fakta pengetahuan: apa yang diinginkan Kant adalah suatu kenaifan: pengetahuan tentang pengetahuan! (Nietzsche, 1968: 530).

Bukan persoalan seberapa kuat benda diyakini. Kekuatan keyakinan bukan pada kriteria kebenaran. Tetapi apa itu kebenaran? Mungkin sebentuk keyakinan yang telah menjadi kondisi hidup? Dalam kasus tersebut, untuk meyakinkan, kekuatan bisa menjadi kriteria, seperti halnya kasualitas (Aporishma 531, Nietzsche, 1968; 494-530).

  1. Webster New International Dictionary, epistemologi diberi definisi sebagai berikut: Epistimology is the theory or science the method and grounds of knowledge, especially with reference to its limits and validity, yang artinya Epistemologi adalah teori atau ilmu pengetahuan tentang metode dan dasar-dasar pengetahuan, khususnya yang berhubungan dengan batas-batas pengetahuan dan validitas atau sah berlakunya pengetahuan itu
  2. Santoso , L.,2012, Epistemologi Kiri, AR-Ruzz Media, Jakarta. Hlm 51-53
  3. Bryan Magee. 2008. The Story of Philosophy. Yogyakarta: Kanisius. Hlm 172-179
  4. Ibid
  5. https://id.wikipedia.org/wiki/Friedrich_Nietzsche

by : Sri Rahayu Wilujeng, 2012, Epistemologi Kiri, AR-Ruzz Media, Jakarta. Hlm 51-59

Daftar Pustaka :

  • Alfons Taryadi, 1989, Epistemologi Pemecahan Masalah Menurut Karl to Nietzsche, Cambridge University Press, Cambridge.
  • Nietzsche, Friedrich, 1968, Twilight of Idols and The Anti-Christ, translated by R.J. Hollingdale, Pinguin Books, Middlesex.
  • _______________, 1968, The Will to Power, translated by Walter Kaufmann and R.J. Hollingdale, Vintae Books, New York.
  • _______________, 1969, Portable Nietzsche, Selected by Walter Kaufmann, Viking Press, New York.
  • _______________, 2000, Thus Spoke Zarathustra, terjemahan Sudarmaji dan Ahmad Santoso, Pustaka Pelajar, Yogyakarta.
  • Sunardi, ST., 1999, Nietzsche, LkiS, Yogyakarta.
  • Verhaak, C. Dan Haryono Imam, 1989, Filsafat Ilmu Pengetahuan: Telaah R. Popper, Gramedia, Jakarta.
  • Bertens, Kees, 1983, Filsafat Barat Abad XX: Inggris-Jerman, Gramedia, Jakarta.
  • Cadello, James, P., Nietzsche’s Radical Hermeneutical Epistemology, dalam International Studies of Philosophy XXIII.2, Scholar Press, Atlanta
  • Fuad Hasan, 1989, Berkenalan dengan Eksistensialisme, Pustaka Jaya, Jakarta.
  • Hardono Hadi, 1994, Epistemologi Filsafat Pengetahuan Kenneth F. Gallangher, Kanisius, Yogyakarta.
  • Kaufmaan, Walter, 1967, ‘Nietzsche, Friedrich’ dalam The Encyclopedia of Philosophy, ed. Paul Edward, Vol. V, Collier Macmillan, London.
  • Magnus, Berd dan Kathleen M. Higgins, 1996, The Cambridge Companison Cara Kerja Ilmu-Ilmu, Gramedia, Jakarta.

The Rose and the Pentagram

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 Children of the Sun” from the Italian manuscript “De Sphaera”, owned by the Sforza family and dated to ca 1460AD. Heinrich Agrippa served as a captain under Maximilian Sforza in 1513-1515AD

Die Rose (the Rose) is a longsword, dussack, rappier and quarterstaff technique described by fencing masters starting from about 1516AD. This striking sequence, as used by several masters including, Andre PaurnfeindtPaul Hektor Mair [1] andJoachim Meyer [2], and several later derivative works [3], has confused some of us as we try to understand the relationship between the name and the application of the technique.

To be able to understand Die Rose I believe we need to understand whatconnotations the renaissance man had to the word rose and with that understanding we can apply it to our interpretations of the technique. The following article might seem like a novel by Dan Brown, but explores some of the ideas the men and women of the Renaissance shared, sometimes in more or less secret societies.

The weak and strong parts of the body for Grappling. From J.A. Schmidt, 1713.

The Tudor Rose, combining the white rose of the House of York and the red rose of the House of Lancaster.

Symbolism regarding the human body and strength & weaknessgeometrics, anglesand actions all tie together in the various illustrations of many fencing treatises of the Renaissance and we need to examine this topic both broadly and deeply. Here, the relationship between the Rose, the Pentagon and the Pentagram are crucial to our interpretations.

Having studied the topic for some time, I would suggest that the execution of this particular striking sequence should be thought of as following the shape of the open-petaled, wild rose rather than that of the cultivated romantic rose that we generally think of today, as the modern type of cultivated roses weren’t introduced into Europe until the late eighteenth century, and up until the mid 16th century the only two roses cultivated were Rosa Gallica and Rosa Alba [4].

Furthermore, from a symbolical outset, with the word rose the renaissance man would more commonly have thought of the kind of heraldic and symbolical rose thatHenry VII combined from the roses of the House of York and the House of Lancasterinto the Tudor Rose. Consequently, I would suggest that the symbolism of the five petals and the angles are of great importance for us to understand in our attempts at understanding Die Rose.

But before exploring this more deeply I would briefly like to expand on the symbolism of the rose as it goes much farther back than this, even as far back as to the ancient Greeks and beyond.

To begin with an interesting astrological and astronomical connection to the Rose is the fact that the passage of Venus over an eight year period, as perceived from Earth, describes the shape of a Rose and a pentagram, a discovery which has been claimed to go as far back as the Akkadians’, with the world’s oldest astrological text, a Venus-tablet from Ninevehand dated to the 17th century BC, and the later Babylonians’, understanding of Ishtar. However, this claim should be taken with a pinch of salt as the Akkadian noting of the eight-year rythm and five synodic periods of Venus do not equate to a proper understanding of the Earth-centric Venus Pentagram. Still, this astronomical curiousity possibly explains her common association with the Rose and the pentagram, but it is difficult to properly trace how early this discovery really was made, despite the numerous theories on the topic.

The passage of Venus from James Ferguson’s “Astronomy Explained Upon Sir Isaac Newton’s Principles”, 1799.

 Regardless, Venus was also called the morning star and the light bringer, in RomanLucifer“, and not until ca 200AD was Satan connected to the name Lucifer by Christian thinkers like Tertullianus and Origenes, perhaps partly due to her also being the evening star.

Furthermore, as early as in ancient Egypt we can trace the roots of the concept of Sub Rosa, as it dates back to the Egyptian Sky god Horus in about 3000BC. Being the Sky god, Horus was also the god of the Sun and the Moon and one of his emblems was the rose. Horus was also the god of War and Hunting and was represented by thefalcon.
The Romans and the Greek regarded Horus as the god of Silence, which led to him, and the rose being associated with secrecy. With this in mind Roman banquets often had roses hanging from, or depictions of roses painted, in the ceiling, implying that what was said under the influence of wine, should remain “sub rosa” ie secret. The same custom was used in the medieval councils where a rose hanging from the ceiling pledged all present to secrecy. The same can even be seen on some Catholic Confession Chairs that are adorned with five-petaled roses.

The early teachings of Kunst des Fechten was of course all meant to be kept secret, all the way up until the time of the printing press, where freyfechter Paurnfeindt is one of the first masters to spread his teachings widely in 1516. This was followed quite successfully by freyfechter Meyer with his treatise of 1570 and possibly we can trace a difference in the attitude towards keeping the Art secret between the two guilds, as few Marxbrüdere ever published printed treatises.
Regardless, here we can’t really apply the meaning of secrecy in the same sense forDie Rose. However, The Rose could be considered to be a deceitful technique where you hide your intentions, similar to the Stürtzhauw or the Fehler, something which Meyer was very fond of, as is apparent from his treatises.

Continuing with the shared symbolism between early Euro-Asian religions, their ties to Christian mysticism and symbolism and the fencing guilds, we see the Persian Sun god Mithra, depicted with a Lion ca 1400BC. Mithra was also the god of Justice and War and he was particularly popular with the Roman soldiers in the form ofMithras who was their patron. Mithras is often equated with Phanes, then depicted as a lion-headed man with golden wings.

The symbols of the Four Evangelists, from the Book of Kells (late 6th to 9th cent.)

 Greek and Roman mythology continues with the Hellenistic Sun god Apollo Helios, brother of Moon goddes Artemis, sometimes depicted riding a griffin and Dionysos depicted in a chariot pulled by a panther, a gryp and a bull, quite similar to the symbols of the Four Evangelistsa lion, an eagle, an ox and an angel.

At about 50BC-350AD we see various depictions of the Egyptian Sun god Horus, the Greek/Roman Sun god Helios, and the Roman Sun god Sol Invictus surrounded by the Zodiac, symbolizing the twelve months and the four seasons. These type of depictions are also seen in Persian books on alchemy and astrology in the 1200-1300s and in Europe with Christ in the center, replacing Helios, at about 1000-1400AD.

It is also interesting to note that Horus’ mother Isis was also associated with the rose and she was often depicted nursing baby Horus, very similar to the imagery of Virgin Mary and baby Jesus who was also strongly associated with the rose [5]. There arenumerous more similarities between Christian mythology and the Egyptian, Greekand Roman religions and there is quite obviously a lot of similar content, as was noted already in antiquity [6].

In the early Renaissance we also see the first images of the masculine Sun and the feminine Moon connected to the opposites of the Lion and the Griffin, locked in eternal struggle with each other.


 The Sun and the Moon fighting, riding a Lion and a Griffin, the symbols chosen by the Marxbrüder and the Freyfechter. – From a Renaissance Rosicrucian Compendium on Alchemy

 Partially due to the Renaissance admiration of the ancient Egyptians, Romans and Greeks, a belief in astrology, alchemy and magic was common in all stratas of society. Referencing to the older pantheons, history and use of symbolism was quite common, as can be seen in the image depicting the Children of the Sun below, a scene that comes in many variants from the mid 1400s to the 1600s, as previously shown.

Planetenkinder der Sonne, by Hans Sebald Beham, ca 1530-40AD.

Not so surprisingly, considering the Renaissance fascination with astrology and alchemy, several fencing masters are known to have included religious, astrological and magical symbols in their treatises, including for instance; Hans Talhoffer who wrote briefly about astrology and the Sun and who showed St. Mark as his patron saint and Achille Marozzo depicted in a circle of magical symbols, as seen below.

Fencing Master Achille Marozzo writing down magical symbols for St. Michael and steel, among other things, in the preface of his fencing treatise Opera Nova of 1536.

Returning to the pentagram the Greek mathematician and philosopher Pythagoras,considered five to be the number of man, due to the fivefold division of the body, and the division of the soul. He also considered the five points of the pentagram to each represent one of the five elements that make up man: fire, water, air, earth, andpsyche. This symbolism, as with much other symbolism has remained both in use and has acted as a great influence on later thinkers, not least in the Renaissance,when the admiration and celebration of the ancient Romans and Greeks was flourishing in the Arts and Sciences.

Furthermore, going at least as far back as the Templar Knights of the 1100s we see the pentagram associated with the rose, symbolically attached to the five wounds of Christ, as well as the idea of Christ being the Alpha and the Omega, since one can draw a pentagram from beginning to end in one continuous (and perpetuous) movement, thus symbolising both eternity and rebirth. [7]

The English are said to have called the pentagram the Endless Knot which is examplified by the quote below and again we see the notion of a single but complex and potentially endless movement that crosses several lines.

“It is a symbol which Solomon conceived once To betoken holy truth, by its intrinsic right, For it is a figure which has five points, And each line overlaps and is locked with another; And it is endless everywhere, and the English call it, In all the land, I hear, the Endless Knot.” [8]

– Legend of Sir Gawain and the Green Knight, Stanzas 27-28 (1380 c.)

A pentagram in a carving from the baptistery of the St. John (Šibenik) Cathedral in Split, Croatia, dated to the 1100s.

Decoration of a pentagram inside a rose, from the Knights Templar church Santa Maria do Olival, built around ca 1150AD in Portugal.

Through all this the rose and the pentagram have strong ties to Christian Renaissance symbolism, Kabbalism and not least Martin Luther and the earlyRosicrucians who were strongly associated with Lutheranism. And perhaps here is where we can understand the Cutting Rose a bit clearer.

Design for a Stained Glass Window for Christoph von Eberstein, by Hans Holbein the Younger, 1522. The rose is part of the Coat of Arms of the Ebersteins. Joachim Meyer dedicated parts of his Ms.82 Rostock-treatise of 1570 to Heinrich von Eberstein.

 With Fechtmeister and Freyfechter Joachim Meyer being a prime example, we know that several of the freyfechtere had strong ties to the Protestant Reformation and especially the Calvinist movement, but even the Marxbrüdere (The Brotherhood of Our dear lady and pure Virgin Mary and the Holy and warlike heavenly prince Saint Mark) were members of a deeply religious organization and both fencing guilds carefully chose their respective identifying crests, each with obvious Christian symbolism; theWinged Lion of St. Mark and the Griffin, respectively. Two distinct opposites in earlier symbolical history, as previously shown.

A marxbrüder praying to his patron saint Saint Mark.

A collage of artwork by Virgil Solis and unknown artist, depicting Freyfechtere with their symbol the Griffin. Dated to the mid 1500s.

With the connections between the Freyfechtere and the Protestant Reformation in mind, it is also interesting to note that the seal of the Protestant reformist Martin Luther was based on a five-petaled Rosa Albaa heart and a cross, where the various elements and colours have specific symbolical meanings regarding Christian virtues and vice.

Furthermore, a deep interest in mathematics and geometry was common during the Renaissance, as evidenced by daVinci’s Vitruvian Man from ca 1487AD. This drawing was made to visualize the ideal human proportions with geometry as described by the Roman architect Vitruvius in his treatise De Archietectura, where he described the human figure as being the chief source of proportion for architecture. The human body, as created by God was simply seen as the ultimate perfection and a synthesis of  Divinity and Humanity.

The seal of Martin Luther in a church in Cobstadt, Thüringen.

 This has also been connected to the idea of the Golden Ratio as can be seen in Agrippa’s human pentagram below and this concept has been used extensively in various aspects of society.

So, what about the pentagram and sword cuts then? Well, historically the pentagram has been drawn both point up and point down and neither related to Satanism as many believe today. But, what is interesting for when interpreting the fencing treatises, is that when a pentagram is overlaid upon a body, it gives diagonal and horisontal lines that pass outside of the body contour with a starting and ending point at the head and corner points that work with several of the guards and cuts.

A pentagram overlaid over a human body, by Heinrich Agrippa.

 Perhaps this is what we are taught when the Rose technique is described – a movement where the point is moved offline, but still, more or less, follows a geometrical line in the shape of the pentagram rose, a movement that is complex and passes more than one line, ending with a blow to the head where the pentagram starts and ends?

A cutting “rose” from Meyer’s von Solms-treatise.

 alternately, it is also possible that the name is meant to cause us to associate our cuts with the shape of the five petals of a rose. Meyer even says this explicitly in his treatise of 1570, when he speaks of the secondary cuts for the dussack, although hisnotion of the Rose is not necessarily exactly the same as that of his predecessors:

Also some receive their names from the shape they resemble in cutting, like the Rose Cut.” [9]

Meyer, Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens, 1570

We can keep this in mind when we read the following excerpts from Andre Paurnfeindt, Paul Hektor Mair and Joachim Meyer.

“Durch ſchiſſen. Durchſchiſſen magſtu auch nemen anſʒ dem hohenort / hav von oben nider vnden durch die Roſen / mit verkertñ henden vnd kurcʒer ſchneid in ſein geſicht / laſʒ kurcʒ ablauffen / mit der langen ſchneidt nachtretten.

Shooting Through. You may also take the shooting through from the high guard, hew from above downwards through the Rose, with reversed hands and short edge in his face, allow this quickly to run off, work after with the long edge.

Paurnfeindt, Ergrundung Ritterlicher Kunst der Fechterey, 1516

Von Anpindñ. Pind dir eyner obñ an prueff ob er herdt oder waych leyt / ligt er herde ſo wind vndñ durch auſʒ der roſñ gegñ ſeinem gſicht / an daſʒ linck or / ſo windeſtu im ſein ſchwerdt auſʒ vñ pleſt in dar mit / ʒuckt er aber vnd ſclecht / vervar obñ mit der verſacʒung

From Binding-on. When one has bound with you from above, then test if he lays on hard or soft, if he lays hard, thus wind under and through the Rose to his face, to the left ear, thus you have wound out on his sword and opened there with, but if he pulls and strikes, drive above with the displacing. 

Paurnfeindt, Ergrundung Ritterlicher Kunst der Fechterey, 1516

Hau von obñ auſʒ dem oxſen gegen ym / vnden durch die roſen vnd leg ym die kurcʒ ſchneid in ſein gſicht / wendt kurcʒ ab vnd ſchlach mit der langen ſchneidt nach

Paurnfeindt, Ergrundung Ritterlicher Kunst der Fechterey, 51V, 1516

Hew from above in the Ox against him, under, through the Rose, and put the short edge in his face, turn away slightly and strike after with the long edge.” [10]

And here is how Mair describes the use of the Rose:

…so trit mit deinem lincken fuoss hinnach unnd halt das gehültz für dem haupt, das der ort zuruckh stee, mit gecreitzgiten aremn unnd haw Im zu seinner rechten seiten. Versetzt er dir das, so raiss Im zu seinner linncker seiten mit deinner kurtzen schneid. Indes winnd dich ubersich auf in der Rosen an seinnen schwert und haw dich inn die zwirch mit gecreitzgiten aremn zu seinner rechten seiten seinnes kopffs.

… then step outward with your left foot and hold the hilt in front of your head such that the point stands to the rear with crossed arms, and strike to his right side. If he displaces this, then travel to his left side with your short edge and then immediately wind upward with the Rose on his sword and strike with the Zwirch with crossed arms to the right side of his head.” (Stucke 15)

Legt er sich also inn das sprechfenster, so winnd auss der Rosen den ort inn sein gesicht, das dem Rechter fuoss vorstee, unnd winnd Im mit der kurtzen schneide zu seinnem Haupt. Indes haw mit lanngen schneid nach seinem Rechten Arm.

If he lies in the Prechfennster like this, wind the point in his face out of the Rosen (Rose) such that your right foot stands forward, then step outward with your left leg, set your right foot behind his left and wind with the short edge to his head. Then immediately strike with the long edge to his right arm.” (Stucke 24)

Item schick dich allso mit dem einwinnden: stannd mit deinnem lincken fuoss vor und halt dit kurtz schneide gögen dem Mann mit creytzweisen hennden, die linnck hannd uber dein rechten arm unnd winnd dich durch Inn der Rosen. Inn dem verfal auf dein linncken seiten, trit mit deinnem Rechten schennckel hinnein und winnd Im zu seinem gesicht.

It happens like this with the Winding In: stand with your left foot forward and hold the short edge opposite the opponent with crossed hands with your left hand over your right arm (as in illustration). Wind through in the Rose and then immediately drop down at your left side, step in with your right leg and wind towards his face.” (Stucke 47) [11]

Paul Hektor Mair, Opus Amplissimum de Arte Athletica, ca 1550

Turning to Meyer here are some of his variations of the Rose:

[Longsword]
“And note when an opponent comes before you who holds his sword extended before him in the Longpoint, or else in Straight Parrying, then send your blade in a circle around from the Middle Guard right around his blade, so that your blade comes almost back to your initial Middle Guard; from there swing the foible powerfully from outside over his arms at his head.” 
(1.40v.1)

“Or when you have thus gone around his blade with the Rose, if he meanwhile should fall in down from above to your opening, then take his blade out with the short edge, that is when you have come for the second time in the Middle Guard; for he will not come so quickly as if by surprise to your opening, but that you will meanwhile come around with the Rose, such that you will come to take him out in plenty of time. And after you have thus taken him out, then let your weapon run around in the air over your head (in order to deceive him), looping for a Circle to the next opening, etc.” (1.40v.2)

“Or in the Onset when you have cut into the Middle Guard on your left, and meanwhile your opponent cuts at you from above, then step well out from his cut toward his right side, and cast your short edge over or outside his right arm at his head; and as you cast in, let your blade shoot well in, either at his head or over his arms. Afterwards pull your sword quickly back up, and cut from your left with the long edge strongly upward at his right arm. From there, attack him further as you will, with such techniques as you will find above or below in this treatise.” (1.40v.3)

“Item, bind him as before, and as soon as the swords connect in the bind, then break through below with the Rose between you and him, and cast the short edge in at his head on the other side.” (1.41r.2)

“Or after you have broken through below from the bind with the Rose, then wrench his sword sideways from the other side with the short edge, so that your hands cross over one another in the air; strike deep with the short edge over at his head.” (1.41r.3)

“Item, bind against his incoming cut, and as soon as the blades connect, push your pommel through under your right arm, stepping at the same time well out toward his left side; and go up with crossed hands, and cut with the long edge through the Rose sideways from below behind his arm at his head.” (1.41r.4)

“Item, when you see that your opponent will bind or cut at you, then send your sword in against him, as if you also intended to bind, and just when the blades are about to connect, push your pommel up quickly, and turn your blade up from below through the Rose, catching his stroke on your long edge, as is shown in the small scene on the right in Image N. After you have thus caught his cut, you can finish this device in two ways. Firstly thus: when the swords have connected, then go right through below with your blade, and wrench his blade toward your right, and let your hands snap around in the air again, or cross over one another, and cut with the short edge strongly at his head.

For the second, when you have caught his sword, then as the swords clash together, step well to his left side, and cut back with the long edge from outside over his left arm at his head.” (1.42r.2- 1.42r.3)

[Dussack]
Rose Cut. If you find an opponent waiting in the Bow, then act as if you intended to cut from above at his head; do not let the cut connect, but go outside his right arm and through below, so that you come around in a circle around his dusack, and let it run off again in the air beside his right, and cut at his face.” (2.11r.2)

[Rappier]
Deceitful Thrust. In the Onset, send a powerful thrust from the right High Guard of the Ox at his face; but as you thrust in, turn your thrust up from below with a broad step forward on your foot, and thrust under his hilt up at his belly. When you correctly reverse this High Thrust into a Low Thrust through the Rose, then it seems at first as if you were thrusting from above, then before he realizes it, you have hit below.” (2.64r.3)

[Quarterstaff]
How you shall take him out upward with the long edge from your left) and thrust through the Rose back up from below from your right at his face: In the Onset, position yourself in the Low Guard on the left as before; if he thrusts in at you, then go up with both arms, and strike out his thrust with the foible of your staff up from your left toward your right with the long edge, so that in striking him out your staff comes right up through; then turn your staff back by your right side up from below, and thrust from that side back up at his face.” (3.20v.1) [12]

Meyer, Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens, 1570

Finally, and perhaps not as distinctly relevant to the topic of the Rose and the Pentagram, it is also interesting to compare the images of Heinrich Agrippa to those of Fechtmeister Joachim Meyer, the treatise Codex Wallerstein and the treatises ofFiore dei LiberiAchille Marozzo and Salvator Fabris, where cutting lines, divisions and weak and strong areas are displayed.

A diagram by Heinrich Agrippa

Cutting lines and the man’s divisions from Codex Wallerstein, from the 1400s. Note the name of Paulus Hector Mair and the 1556 date inbetween the legs

 The similarities between the images in the treatises of Fiore Dei Liberi and Filippo Vadi and the images showing the correlations between the signs of the Zodiac and the organs (called Melothesia, astrological medicine), for instance in Ketcham’sFasciculus Medecinae from 1495AD is striking, but there are likely no deeper relations involved here other than a common pictographical form of expression, as the idea of dividing a man into different sections and attaching symbolism to the various body parts and organs can be seen in both astrological and medical treatises as well as in illustrations in fencing treatises, going all the way back to the Middle Ages.

It is noteworthy though, that Tobias Stimmer, one of the illustrators of Fechtmeister Joachim Meyer’s 1570 treatise Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens also made a portrait of the aforementioned Heinrich Agrippa in 1587.

Cutting lines from Meyer’s 1570 treatise.

Still, we should also keep in mind that this is a time when mathematics and geometrywere highly influential on warfareartillery, architecture, geometricscity & fortification planning and not least in the Art of Fencing.

This can also be seen in Meyer’s illustrations where the geometrically decorated floor patterns teach us correct stepping and use of angles in our fencing. This geometrical approach to the Art of Fencing would soon be a very common tool for teaching as can be seen in many treatises of the Verdada Destreza tradition, but also fencing masters like the Dutch Gerard Thibault with his Academie de l’Espée of 1630 and many others.

From the Fiore dei Liberi treatise Pisani-Dossi MS (page 16r,) dated to 1409AD

Finally, if we are to fully understand the medieval and renaissance fencing treatises and especially the culture of the fencers and the fencing guilds and the mentality of the fencers, then concepts like the four humours & the four temperaments, astrology & the planetenkinder, and many other important Christian, hermetical, mystical and even alchemical symbols are important to understand. And when we understand these we will be better equipped to understand the concepts behind the techniques and their terminology at a more profound level, thus hopefully being more likely to succeed in what we aspire to do; make the Historical European Fighting Arts come alive again.

I would like to thank Chris Vanslambrouck of the Meyer Frei Fechter Guild for the delightful conversations we have had regarding Meyer, the Freyfechtere, alchemy and many other related topics, and for his insightful comments on this article while proofreading it. I owe you.

By : Roger Norling


References

1. See Stucke 15, 23 & 47 in Opus Amplissimum de Arte Athletica.

2. See regarding Mittelhut and Langort in his 1570 treatise Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens.

3. Jakob SutorChristian Egonolph (editor) and Lienhart Sollinger.

4. According to Lars Åke Gustavsson’s Rosor för nordiska trädgårdar, the Medieval/Renaissance roses “came” to Europe in the following order:

??? Rosa Alba
1310 Rosa Gallica Officinalis
1500 Rosa Gallica
1500 Rosa Villosa
1542 Rosa Foetida
1551 Rosa Rubignosa
1581 Rosa (Gallica Officianis) Mundi
1581 Rosa Major
1583 Rosa Frankfurt
1590 Rosa Bicolor
1596 Rosa Tuscany
1597 Rosa Majalis Foecund

Not all of them spread to all of Europe and when they arrived to different countries of course varied greatly.

5. See Jesus Christ in Comparative Mythology, Wikipedia.org <http://en.wikipedia.org/wiki/Jesus_Christ_in_comparative_mythology> (retrieved  10 July 2012)

6. See The Christian Symbolism of the Rose, Rev. Theodore A. Koehler, S.M <http://campus.udayton.edu/mary/rosarymarkings36.html> (retrieved 18 July 2012)

7. See for example 12th cent. Church of Santa Maria do Olival built by the Order of the Knights Templar in Portugal. The church was used as a burial place for the Knights Templar of Tomar and 22 Master Templars are buried there. The church has several examples of five-petaled roses and pentagrams used for decoration, both in the architecture itself and on gravestones.

8. See Stone, B. (1974) Sir Gawain and the Green Knight. (p 45) Penguin Group.

9. From Joachim Meyer’s Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens of 1570,  2.9R, as translated by Dr. Jeffrey Forgeng.

10. Translated by Kevin Maurer of the Meyer Frei Fechter Guild.

11. Translated by Keith P Myers of the Black Swan Fechtschule.

12. From Joachim Meyer’s Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens of 1570, as translated by Dr. Jeffrey Forgeng.

Sources

Fisher, Celia, Flowers of the Renaissance, Frances Lincoln, UK/J. Paul Getty Museum; 1 edition <http://books.google.se/books?id=zDJ8Sj3fGcQC&lpg=PA21&ots=kJ8mJwCF3s&dq=roses%20in%20the%20renaissance&hl=sv&pg=PA21#v=onepage&q=roses%20in%20the%20renaissance&f=false>(May 24, 2011)

Marozzo, Achille: Opera Nova. 1536, Modena <http://www.hroarr.com/manuals/fiore/Marozzo-Achille-Opera nova-Mutina-1536-Res-4-Gymn-26.pdf>

Meyer, Joachim: Gründtliche Beschreibung der freyen Ritterlichen und Adelichen Kunst des Fechtens.  1570. Strassburg <http://www.hroarr.com/manuals-books/new-manual-section/?did=2>

History of the Rose. Herbs2000.com. <http://www.herbs2000.com/flowers/r_history.htm> (16 July, 2012)

Gustavsson, Lars Åke, Rosor för nordiska trädgårdar, Natur och Kultur, Sweden (1998)

The Pentagram in Depth, Symboldictionary.net <http://symboldictionary.net/?p=1893> (16 July, 2012)