Power Analysis for Moderator Effects in Longitudinal Cluster Randomized Designs

• In Event: AERA Poster Session 4
  In Poster Session: Division D Section 2 Poster Session 1

Abstract

Cluster randomized control trials often incorporate a longitudinal component where for example students are followed over time and student outcomes are measured repeatedly. Besides examining how the main effects of the intervention change over time, educational researchers are also interested in whether the effects of an intervention differ conditional on individual or cluster moderator variables such as gender, ethnicity, or school urbanity. This study provides methods of power analysis to detect moderator effects in two and three-level longitudinal cluster randomized designs. Power computations take into account clustering effects, the number of measurement occasions, and the impact of sample sizes at different levels, covariates effects, and the variance of the moderator. An illustrative example shows how power is computed.

Authors

• Wei Li, University of Florida

• Spyros Konstantopoulos, Michigan State University