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Article
Analytic Approaches for Assessing Long-Term Treatment Effects: Examples of Empirical Applications and Findings
Evaluation Research
  • Stephen C. Messer, Nova Southeastern University
  • Yih-Ing Hser
  • Haikang Shen
  • Chih-Ping Chou
  • M. Douglas Anglin
Document Type
Article
Publication Date
4-1-2001
Disciplines
Peer Reviewed
1
Abstract

Analytic approaches, including the structural equation model (autoregressive panel model), hierarchical linear model, latent growth curve model, survival/event history analysis, latent transition model, and time-series analysis (interrupted time series, multivariate time-series analysis) are discussed for their applicability to data of different structures and their utility in evaluating temporal effects of treatment. Methods are illustrated by presenting applications of the various approaches in previous studies examining temporal patterns of treatment effects. Recent advancements in these longitudinal modeling approaches and the accompanying computer software development offer tremendous flexibility in examining long-term treatment effects through longitudinal data with varying numbers and intervals of assessment and types of measures. A multimethod assessment will contribute to a more complete understanding of the complex phenomena of the long-term courses of substance use and its treatment.

DOI
10.1177/0193841X0102500206
Citation Information
Stephen C. Messer, Yih-Ing Hser, Haikang Shen, Chih-Ping Chou, et al.. "Analytic Approaches for Assessing Long-Term Treatment Effects: Examples of Empirical Applications and Findings" Evaluation Research Vol. 25 Iss. 2 (2001) p. 233 - 262 ISSN: 0193-841X
Available at: http://works.bepress.com/stephen-messer/7/