Robust analysis of a mixed-effect model for a multicenter clinical trial.
We consider a multicenter clinical trial with treatments as fixed effects and centers and residuals as bivariate and univariate random effects, respectively. There exist situations where it is difficult to justify the conventional normality assumptions for the random components. Following Khatri and Patel (Commun. Stat.-Theory Methods 1992, 21, 21-39), we propose the weighted least-squares (WLS) method and two bootstrap methods, percentile and BCa, that are robust to the departure from normality. Through a simulation study, we compare WLS and bootstrap confidence intervals for the treatment difference. While all three methods give confidence intervals with desired coverage rates, the WLS method gives shorter intervals. We also propose a bootstrap method that is robust to outliers. A numerical example is given to illustrate the methodology.
Patel
Harji I
HI
Center for Biostatistics, College of Health and Professional Studies, Georgia Southern University, Statesboro 30460, USA. hipatel@gsaixz.cc.gasou.edu
D003198:Computer Simulation; D016001:Confidence Intervals; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D015337:Multicenter Studies as Topic / Q000379:methods / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data