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Estimating Causal Treatment Effects from Longitudinal HIV Natural History Studies Using Marginal Structural Models

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  • Hyejin Ko
  • Joseph W. Hogan
  • Kenneth H. Mayer

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  • Hyejin Ko & Joseph W. Hogan & Kenneth H. Mayer, 2003. "Estimating Causal Treatment Effects from Longitudinal HIV Natural History Studies Using Marginal Structural Models," Biometrics, The International Biometric Society, vol. 59(1), pages 152-162, March.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:1:p:152-162
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    File URL: http://hdl.handle.net/10.1111/1541-0420.00018
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    References listed on IDEAS

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    1. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
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    Cited by:

    1. Sean Yiu & Li Su, 2022. "Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models," Biometrics, The International Biometric Society, vol. 78(1), pages 115-127, March.
    2. Mélanie Prague & Daniel Commenges & Jon Michael Gran & Bruno Ledergerber & Jim Young & Hansjakob Furrer & Rodolphe Thiébaut, 2017. "Dynamic models for estimating the effect of HAART on CD4 in observational studies: Application to the Aquitaine Cohort and the Swiss HIV Cohort Study," Biometrics, The International Biometric Society, vol. 73(1), pages 294-304, March.
    3. Yana Kucheva, 2014. "The Receipt of Subsidized Housing across Generations," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(6), pages 841-871, December.

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