Dunnett's Test

Multiple comparison procedures are fundamental in experimental research. Dunnett’s test, which compares multiple treatments to a single control, is particularly common in laboratory studies. When multiple comparisons are made, proper statistical methods are essential to control false positives. This article demonstrates how the number of comparisons affects p-values in Dunnett’s test, implements the procedure in R, and discusses strategies to improve statistical power.