Robust Covariate Control in Cluster-Randomized Trials with MPLUS and WinBUGS

• Activity Number: 142
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Section on Survey Research Methods
• Author(s): Jiaquan Fan*+
• Companies: Westat
• Keywords: Cluster-randomized trials ; multi-level modeling ; Bayesian inference using Gibbs Sampling

Abstract

Two more statistical software packages, MPLUS and WinBUGS, were tested as a continuation of a previous study of analysis method/software robustness in the analysis of clustered data. We want to evaluate robustness in the context of a randomized complete block design, where each "plot" is a small group of children at the same nursery school and a series of measurements of each child are made. We constructed a series of super populations in which the standard assumptions of hierarchical (mixed effects) linear models were violated. The results were compared with HLM, SUDAAN, PROC MIXED and a semi-parametrical analysis of variance procedure we tested before.