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Research Article
Simple Power and Sample Size Estimation for Non-Randomized Longitudinal Difference in Differences Studies
Author(s): Yirui Hu and Hoover DRYirui Hu and Hoover DR
Intervention effects on continuous longitudinal normal outcomes are often estimated in two-arm pre-post interventional studies with b≥1 pre- and k≥1 post-intervention measures using “Difference-in-Differences” (DD) analysis. Although randomization is preferred, non-randomized designs are often necessary due to practical constraints. Power/sample size estimation methods for non-randomized DD designs that incorporate the correlation structure of repeated measures are needed. We derive Generalized Least Squares (GLS) variance estimate of the intervention effect. For the commonly assumed compound symmetry (CS) correlation structure (where the correlation between all repeated measures is a constantρ) this leads to simple power and sample size estimation formulas that can be implemented using pencil and paper. Given a constrained number of total timepoints (T), .. Read More»
Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report