t-test for Independent Samples - More Complex Group Comparisons

It often happens in research practice that you need to compare more than two groups (e.g., drug 1, drug 2, and placebo), or compare groups created by more than one independent variable while controlling for the separate influence of each of them (e.g., Gender, type of Drug, and size of Dose). In these cases, you need to analyze the data using Analysis of Variance, which can be considered to be a generalization of the t-test. In fact, for two group comparisons, ANOVA will give results identical to a t-test (t2 [df] = F[1,df]). However, when the design is more complex, ANOVA offers numerous advantages that t-tests cannot provide (even if you run a series of t-tests comparing various cells of the design).