On the analysis of repeated measures over time in medical, pharmacological, and behavioral research

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Abstract
Studies comparing different treatments over time using repeated measures on a wide variety of outcome variables are very common in the research literature. Unfortunately, they are rarely analyzed appropriately, at least from the standpoint of controlling the type I error rate (false rejection of the null hypothesis). As a consequence, many of the positive findings reported in such studies may be incapable of replication. The present article reviews the logical and statistical problems involved, emphasizes the importance of controlling the experimentwise error rate regardless of the research design employed, and presents an integrated, multivariate strategy for dealing with the several issues raised. Resolution of these issues is essential if the “fictional” content of research journals is to be kept within reasonable bounds.