An introductory video tutorial is available at: http://neolab.stat.ucla.edu/cranstats/RDSAnalyst_tutorial.mov
Below is step-by-step walk though the video.
1. Reading the NY Jazz dataset from RDSAT
- Select the Open RDS Data/Load Data from the RDS Data menu.
- Use the dialog boxes to select the file
nyjazz.rdsat from the directory
RDS Analyst Example Data Sets which is on your Desktop. (Hint: If it does not appear, in Windows look in
C:\Program Files\RDS Analyst\R-2.15.0\library\RDSdevelopment\extdata. For Mac, look for
~/workspace/org/bin/RDSdevelopment/inst/extdata/nyjazz.rdsat with possible adjustment depending on the name and location of your workspace.)
- The data is read in as a RDS format and with a rds preface to indicate it is an RDS data set (rather than just a regular spread sheet, say).
2. Looking and editing the data in the spread sheet (the Data Viewer)
- Under the Packages & Data menu, open the Data Viewer and note that the (rds) nyjazz data set is selected in the Data Set menu (center of the window pane). If you load more than one data set you can select the one to view here.
- Here you can look at the data in spreadsheet format. There is more information on the "Data Viewer" here http://www.deducer.org/pmwiki/pmwiki.php?n=Main.TheDataViewer
- On the left side of the spreadsheet are three tabs:
- "Data View" which is the current spreadsheet view
- "Variable View" which summarizes the variables and their properties.
- "RDS" where you can add information about the data set (such as estimates of the population size). It is OK to go with the default values for now.
- Click on the Variable View tab. Click the value for Gender.MF. Under the Type column select Factor. Repeat for Race.WBO., Airplay.yn., and Union.yn.. This makes sure that the program recognizes these as categorical variables.
- Click on the RDS tab. Click the value for Mid in the Population Size Estimate section. Enter an estimate of the population size for the NY jazz population. While this is unclear, a possible value is 20000. It is used in the computations, but they are somewhat insensitive to it as long as it is not close to the sample size.
3. Looking at the data (the Plots menu)
- From the RDS Sample menu select Plot Recruitment Tree. Select Run. The plot will appear in a new graphics window (called "JavaGD (2)", ha ha). This plots the recruitment trees, labeling each node by its ID. There are options in the dialog box you can play with to get different views. Select the "File" menu from the "JavaGD (2)" window to save the file as a PDF, JPG, etc.
- Select Diagnostic Plots from the RDS Sample menu. Unselect the Recruitment tree box and select the Network size by wave box. Click Run. This is a plot of the network size distributions by the wave number of the respondent.
4. Looking at the data (the Analysis menu)
This is for exploratory data analysis.
- Select Contingency Tables from the Analysis menu.
- Select Gender.MF. as the Row and Race.WBO. as the Column
- Click the Run button
- Look in the Console window for the results. On top of the console window there are two tabs Console view and Element View. The Console view gives a continuous view of the commands sent to the <u>RDA Analyst</u> engine. The Element View shows the results of each command separately, and is usually better. Click on the Element View tab.
- The results are in a contingency table output followed by a test of independence of the two factors.
5. Analyzing the data (the RDS Population menu)
- Select Frequency Estimates from the RDS Population menu.
- Select Gender.MF. as the Variables using the arrow buttons and specify a population size estimate.
- Click the Run button.
- Look in the Console window for the results. This uses a computationally-intensive algorithm to compute the confidence interval and will take 20 seconds or more to return output to the Console window. The output is a summary table with the point estimate and 95% confidence intervals. it also reports the design effect, standard error and the sample size (the last is adjusted for any missing values).
6. Saving the data
- To save the data and any edits to it in a file, choose Save Data from the File menu in Console. You can save it anywhere. It will save it with a
robj suffix so that next time you read it in the program will know that it is an RDS data set and not ask you to reenter all the information again.
7. Saving the results
- To save the results in a file, choose Save from the File menu in Console, and make sure Results is selected from the Options:. You will need to add an extension to the file name, and we suggest <tt>txt</tt> (e.g., the file name <tt>rdsat_simple.txt</tt>). This should be open with, e.g., <tt>WordPad</tt> under Windows as it is a simple text file.
- To save the commands used to create the output in a file, choose Save from the File menu in Console, and make sure Commands is selected from the Options:.
- To save the complete output (results interspersed with the commands that produced them) in a file, choose Save from the File menu in Console, and make sure Complete output is selected from the Options:.