This function is only necessary when working with unbalanced panel data. (That is: there are differing numbers of observations per person/participant/ID.) Here, data can be extracted from unbalanced panel datasets without programming knowledge and with just a few clicks.
Among other things: creation of new variables, handling of missing values, adjustment of the scale level, filtering.
Here, the entire dataset (i.e., all combinations of variables) is tested using inferential statistics. Cross-sectional or panel datasets can be used. The appropriate tests are selected based on criteria such as scale level, normality, and heteroskedasticity. Additionally, models or survival analyses can be created. The results are presented as publication-ready tables, figures, and text.
