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Evaluation of Hiv Risk Reduction Intervention Programs Via Latent Growth Model

Author

Listed:
  • Jichuan Wang

    (Wright State University)

  • Harvey A. Siegal

    (Wright State University)

  • Russel S. Falck

    (Wright State University)

  • Robert G. Carlson

    (Wright State University)

  • Ahmmed Rahman

    (Wright State University)

Abstract

The latent growth model (LGM) has drawn increasing attention in behavioral studies using longitudinal data. The LGM captures the level and trajectory of behavior change, variation in both the initial status and the trend of behavior change, as well as the time-ordered covariation between the initial status and change. This study demonstrates how the LGM can be applied in the evaluation of intervention programs targeting HIV risk behavior among drug users. Multigroup piecewise latent growth models were fit to longitudinal data with three repeated response measures.

Suggested Citation

  • Jichuan Wang & Harvey A. Siegal & Russel S. Falck & Robert G. Carlson & Ahmmed Rahman, 1999. "Evaluation of Hiv Risk Reduction Intervention Programs Via Latent Growth Model," Evaluation Review, , vol. 23(6), pages 648-662, December.
    • Handle: RePEc:sae:evarev:v:23:y:1999:i:6:p:648-662
    DOI: 10.1177/0193841X9902300604
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    References listed on IDEAS

    as
    1. William Meredith & John Tisak, 1990. "Latent curve analysis," Psychometrika, Springer;The Psychometric Society, vol. 55(1), pages 107-122, March.
    2. Bengt Muthén & David Kaplan & Michael Hollis, 1987. "On structural equation modeling with data that are not missing completely at random," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 431-462, September.
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