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Analytic Approaches for Assessing Long-Term Treatment Effects

Author

Listed:
  • 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)

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.

Suggested Citation

  • Yih-Ing Hser & Haikang Shen & Chih-Ping Chou & Stephen C. Messer & M. Douglas Anglin, 2001. "Analytic Approaches for Assessing Long-Term Treatment Effects," Evaluation Review, , vol. 25(2), pages 233-262, April.
    • Handle: RePEc:sae:evarev:v:25:y:2001:i:2:p:233-262
    DOI: 10.1177/0193841X0102500206
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    References listed on IDEAS

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    Cited by:

    1. Cheung, Chau-kiu & Ngai, Steven Sek-yum, 2013. "Reducing youth's drug abuse through training social workers for cognitive–behavioral integrated treatment," Children and Youth Services Review, Elsevier, vol. 35(2), pages 302-311.

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