This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 288
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Social Statistics Section
Abstract - #306434
Title: A Multilevel Modeling Approach to Investigating Treatment Effect Variability in Randomized Longitudinal Experiments
Author(s): Joseph Rausch*+
Companies: University of Cincinnati College of Medicine/Cincinnati Children's Hospital
Address: 3333 Burnet Ave, Cincinnati, OH, 45230,
Keywords: multilevel modeling ; randomized clinical trial ; longitudinal data analysis ; treatment effect variability
Abstract:

The standard approach to investigating treatment effects on continuous outcomes in randomized experiments is via the average (i.e., mean) treatment effect. However, averages can hide important variation in the treatment effect and can potentially mislead researchers and clinicians alike when determining the appropriate treatment for a particular individual. Statistical methods which directly address the possibility of variance in the treatment effect should be employed to better understand these effects at the individual level. The present talk discusses such an approach for investigating treatment effect variability in randomized longitudinal experiments using multilevel modeling. Hypothesis testing and estimation, along with the assumptions underlying these approaches, are discussed to assess in what scenarios they are appropriate in applied research.


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