Randomization, counterbalancing, and crossover design tool

This tool is intended to solve the problem of appropriately generating randomized, counterbalanced research designs. In, at the very least, human participant research, researchers generally have research questions which requires investigating two or more sets of conditions in various populations. For example, a researcher might want to investigate how various physical activity behaviors (let's say weight lifting, running, and sedentary behaviors) affect the muscle hypertrophy of men and women. Perhaps they further decide to determine the magnitude of effect of various nutritional interventions on these results (for example, using a post-workout protein drink or a placebo).

To avoid potential biasing of treatment effects, the researcher must counterbalance and randomize all conditions of their study. As the number of conditions and treatments grow (along with the number of groups to which such treatments apply), this becomes a much more laborious task.

In short, this tool aims to alleviate such mundane tasks so that the researcher can focus on what is most important - getting research done.