Overview of Data Output
When DirectRT finishes running an input file, it writes the data file to a "data" subdirectory located in the same folder as the input file. If the data subdirectory does not exist, DirectRT creates it. Since DirectRT will anticipate you running multiple subjects with the same input file it will create a subfolder with the name of your input file. In this folder will be the data for each subject you run using that input file.
For example, if you have an input file called:
Then DirectRT will create a folder:
And then it will create a data file for each subject. For example, data from Subject 34 and Subject 35 would be in the following files, respectively:
These data files are short form data files that are useful for most purposes. DirectRT also creates log data files that contain much more information if you need it (e.g., exactly how long each stimulus was displayed). These files are placed in a log subfolder. For example,
c:\input files\data\input 1\log\log_35.csv
An Alternative Method
If you have many different versions of an input file and don't want the data from each one put in a separate folder then you can do the following: Name your input files with common name (e.g., input) and then use an underscore and an ID, e.g., input_1.csv, input_2.csv, etc.). DirectRT will create folders in the data directory using the common name and will place any data from input files sharing that common name in the same folder (e.g., c:\input files\data\input). You will be able to identify exactly which input file the subject received because it's written to the log data file.
Analyzing DirectRT Data
DirectRT data files are vertical, that is, each subject has many rows of data rather than having all of their responses placed on a single line (e.g., like MediaLab data files). This creates a certain challenge for analysis. While DirectRT is not an analysis program there are a few things to know which might help you if you're new to this type of data file.
A common approach is to use the DirectRT filemerge program (see below) to create a large single data file from the many individual files (be sure to use the option to skip the first line on each file which is the variable name header). Then rename this large file with a .csv extension so that you can import it into SPSS. Once the .csv file is in SPSS, you can use the SPSS COMPUTE and TRANSFORM functions to separate the data into appropriate columns and create the variables you want. This is often easier if you have used comment columns to indicate your within subject conditions. Then the trick is to apply SPSS's AMALGAMATE function which can do the rest for you. Separating according to subject, you can request means and standard deviations to be calculated and imported into a new file, and voila: a dataset with each subject as a row and the means and standard deviations of relevant variables as columns. Be sure to make a copy of the SPSS syntax so that you can use the technique over and over again as needed.
Merging Data Files
If you're looking for a convenient method for merging the data files that does not require SPSS, DirectRT offers a utility called FileMerge (..\DirectRT\FileMerge\FileMerge.exe) to do this rather painlessly. Essentially all you have to do is drag the files you want to merge into the FileMerge window and select "Merge Files" from the File menu. If you like, you can also save the list of files to merge them again later. A quick tutorial on FileMerge is available by clicking on the FileMerge Help menu. You can also start FileMerge by selecting a "Merge Data Files" from the DirectRT Tools menu.
Block ID for rules regarding which trial data are written to the file