Construction of efficient classes of circular balanced repeated measurements designs with R

Abstract

Pharmacology, medicine, psychology, and the animal sciences all employ repeated measurement designs (RMDs). However, RMDs may experience carryover effects, which are the primary cause of bias in treatment effect estimation. In order to eliminate the carryover effects for odd v (the number of treatments), minimal circular balanced and strongly balanced repeated measurement designs (RMDs) are the ones that should be used. The minimal circular partially balanced and weakly balanced RMDs are used for even v. In order to obtain these important classes of minimal circular RMDs in periods of equal, two, and three different sizes, an R-based algorithm is developed in this article. The newly developed algorithm has made so simple the construction of balanced RMDs and their generalized classes. As a result, it is a novel piece of research.