Assessing program effects in the presence of treatment-baseline interactions: a latent curve approach.

  title={Assessing program effects in the presence of treatment-baseline interactions: a latent curve approach.},
  author={Siek Toon Khoo},
  journal={Psychological methods},
  volume={6 3},
Methods for assessing treatment effects of longitudinal randomized intervention are considered. The focus is on modeling the nonlinear relationship between treatment effects and baseline often observed in prevention programs designed for at-risk populations. Piecewise linear growth modeling was used to study treatment effects during the different periods of development. A multistep multiple-group analysis procedure is proposed for assessing treatment effects in the presence of nonlinear… CONTINUE READING

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View 5 Excerpts
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Unpublished doctoral dissertation, • 1997
View 1 Excerpt

The metric matters: The sensitivity of conclusions about growth in student achievement to choice of metric

H SeltzerM., K A.Frank, A S.Bryk
Educational Evaluation and Policy Analysis, • 1994

Using covariance structure analysis to detect correlates and predictors of individual change over time

J. B. Willett, A. G. Sayer
Psychological Bulletin, • 1994
View 2 Excerpts

Analyzing preventive trials with generalized additive models.

American journal of community psychology • 1993
View 1 Excerpt

Latent variable modeling of growth with missing data and multilevel data

B. O. MuthŽn
Multivariate analysis : Future directions • 1993

Selection and predictive validity with latent variable structures

B. O. MuthŽn, J. W. Hsu
British Journal of Mathematical and Statistical Psychology, • 1993

Hierarchical linear models: Applications and data analysis methods

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