The video below demonstrates inverse probability of treatment weighting in longitudinal studies when the treatment may occur more than once.
R code for propensity score analysis of time-varying treatments
chapter_9_longitudinal_ps_analysis.r | |
File Size: | 8 kb |
File Type: | r |
chapter_9_part2_longitudinal_ps_analysis_with_covariate_balancing_propensity_score.r | |
File Size: | 3 kb |
File Type: | r |
Data for example propensity score analysis for time-varying treatments
chapter_9_long_data_imputed.rdata | |
File Size: | 549 kb |
File Type: | rdata |
Related research:
Leite, W. L. (2015). Latent growth modeling of longitudinal data with propensity score matched groups In Wei Pan, & Haiyan Bai. Propensity Score Analysis: Fundamentals, Developments, and Extensions, (pp. 191-216.) New York: Guilford.
Leite, W. L., Sandbach, R., Jin, R., MacInnes, J., & Jackman, G. A. (2012). An Evaluation of Latent Growth Models for Propensity Score Matched Groups. Structural Equation Modeling. 19, 437–456.
Leite, W. L. (2015). Latent growth modeling of longitudinal data with propensity score matched groups In Wei Pan, & Haiyan Bai. Propensity Score Analysis: Fundamentals, Developments, and Extensions, (pp. 191-216.) New York: Guilford.
Leite, W. L., Sandbach, R., Jin, R., MacInnes, J., & Jackman, G. A. (2012). An Evaluation of Latent Growth Models for Propensity Score Matched Groups. Structural Equation Modeling. 19, 437–456.
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