Co-Principal Investigator: Natesan Batley, Prathiba

An important function of effect size measures is to represent the results of studies in a manner that is as comparable as possible. Single-case designs are more difficult to compare across studies, given the typically low number of participants involved in such studies. The purpose of this project is to develop design comparable effect size measures for alternating treatments designs and for changing criterion designs.

The research team will first derive the approximate sampling distributions of the design comparable effect sizes. They will then evaluate the accuracy of the distributions using Monte Carlo simulations of three different estimators of the effect size each for alternating treatments designs and for changing criterion designs. After any necessary mathematical adjustments and reevaluation, the researchers will develop software for calculating the effect size estimates; the software will be available in R and as a Shiny app online. Other products include  manuscripts in methodological journals  to support additional development of design comparable effect sizes and manuscripts in applied journals  to facilitate the use of the effect size estimates by applied researchers.