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

Abstract Details

Activity Number: 293
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract - #307647
Title: Understanding Time-Varying Moderation Effects When Evaluating Substance Abuse Treatment Modalities Using Structural Nested Mean Models
Author(s): Daniel Almirall*+ and Dan Nettleton and Cha-Chi Fan and Beth Ann Griffin and Daniel F. McCaffrey
Companies: University of Michigan and Iowa State University and RAND Corporation and RAND Corporation and RAND Corporation
Address: 2204 ISR, Ann Arbor, MI, ,
Keywords: substance abuse ; causal inference ; structural nested mean model ; longitudinal data ; effect moderation ; effect modification
Abstract:

Large treatment effects are difficult to find when evaluating the effects of substance abuse treatment modalities among adolescent clients. It is hypothesized that client heterogeneity could explain this in so far as the effects of treatment may be greatest for a subgroup of patients. Most analyses examining moderation effects of treatment focus on moderation by time-invariant characteristics of patients measured at baseline. However, most clients in substance abuse treatment experience multiple treatment episodes over time, and time-varying moderators of treatment effects (e.g., severity of substance use problems after different treatment episodes) may exist. We employ the structural nested mean model to estimate the causal effect of additional treatment on longitudinal substance use outcomes, and to identify possible time-varying moderators of these effects.


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