Analytic Approaches for Assessing Long-Term Treatment Effects

Yih-Ing Hser, Haikang Shen, Chih-Ping Chou, Stephen C. Messer and M. Douglas Anglin
Additional contact information
Yih-Ing Hser: UCLA Drug Abuse Research Center
Haikang Shen: UCLA Drug Abuse Research Center
Chih-Ping Chou: University of Southern California
Stephen C. Messer: Westat
M. Douglas Anglin: UCLA Drug Abuse Research Center

Evaluation Review, 2001, vol. 25, issue 2, 233-262

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.

Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:sae:evarev:v:25:y:2001:i:2:p:233-262

DOI: 10.1177/0193841X0102500206

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