Analysis of data from group-randomized trials with repeat observations on the same groups.
This study used Monte Carlo simulations to evaluate the performance of alternative models for the analysis of group-randomized trials having more than two time intervals for data collection. The major distinction among the models tested was the sampling variance of the intervention effect. In the mixed-model ANOVA, the sampling variance of the intervention effect is based on the variance among group x time-interval means. In the random coefficients model, the sampling variance of the intervention effect is based on the variance among the group-specific slopes. These models are equivalent when the design includes only two time intervals, but not when there are more than two time intervals. The results indicate that the mixed-model ANOVA yields unbiased estimates of sampling variation and nominal type I error rates when the group-specific time trends are homogenous. However, when the group-specific time trends are heterogeneous, the mixed-model ANOVA yields downwardly biased estimates of sampling variance and inflated type I error rates. In contrast, the random coefficients model yields unbiased estimates of sampling variance and the nominal type I error rate regardless of the pattern among the groups. We discuss implications for the analysis of group-randomized trials with more than two time intervals.
Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis 55454, USA.
D M
DM
Murray
P J
PJ
Hannan
R D
RD
Wolfinger
W L
WL
Baker
J H
JH
Dwyer
D000704:Analysis of Variance; D015982:Bias; D003198:Computer Simulation; D003625:Data Collection / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*