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date: 30 May 2020

Abstract and Keywords

Determining if a treatment "works" requires proper research design and statistical analysis. The randomized clinical trial (RCT) is the preferred research design to determine the efficacy of a given treatment. A variety of strategies exist for analyzing data from RCTs that follow a pretreatment, posttreatment, follow-up (PPF) design. This chapter reviews common data analytic approaches and discusses the relative advantages and disadvantages of each. The chapter also reviews when to apply each of these strategies for analyzing data within a PPF design. Analyses reviewed include the analysis of variance (ANOVA), multivariate analysis of variance (MANOVA), analysis of covariance (ANCOVA), multivariate analysis of covariance (MANCOVA), and hierarchical linear modeling (HLM).

Keywords: Randomized clinical trial (RCT), clinical research, analysis of variance (ANOVA), analysis of covariance (ANCOVA), multivariate analysis of covariance (MANCOVA), hierarchical linear modeling (HLM)

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