When using a within-subjects research design, the database must be structured in a fashion that allows for comparison of several different observations of an outcome moving forward in time or within-subjects.
The first column of the within-subjects database should contain a unique numerical de-identifier for each study participant. Most research studies require participant confidentiality and anonymity. The de-identifer takes care of this ethical issue. The ID also allows for data entry and data validation.
Each observation of the outcome has in its own column in a within-subjects database. The observations should be presented in their actual order as taken in the reseach study.
Be sure to create a data dictionary alongside the within-subjects database so that all researchers will know the codifications of categorical variables and what specific types of outcomes will be analyzed using the within-subjects database..
The first column of the within-subjects database should contain a unique numerical de-identifier for each study participant. Most research studies require participant confidentiality and anonymity. The de-identifer takes care of this ethical issue. The ID also allows for data entry and data validation.
Each observation of the outcome has in its own column in a within-subjects database. The observations should be presented in their actual order as taken in the reseach study.
Be sure to create a data dictionary alongside the within-subjects database so that all researchers will know the codifications of categorical variables and what specific types of outcomes will be analyzed using the within-subjects database..
Within-subjects database
Click on the Download Database and Download Data Dictionary buttons for a configured database and data dictionary for within-subjects statistics.