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Estimating Mean Response as a Function of Treatment Duration in an Observational Study, Where Duration May Be Informatively Censored

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  • Brent A. Johnson
  • Anastasios A. Tsiatis

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  • Brent A. Johnson & Anastasios A. Tsiatis, 2004. "Estimating Mean Response as a Function of Treatment Duration in an Observational Study, Where Duration May Be Informatively Censored," Biometrics, The International Biometric Society, vol. 60(2), pages 315-323, June.
    • Handle: RePEc:bla:biomet:v:60:y:2004:i:2:p:315-323
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2004.00175.x
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    References listed on IDEAS

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    1. Satten, Glen A. & Datta, Somnath & Robins, James, 2001. "Estimating the marginal survival function in the presence of time dependent covariates," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 397-403, October.
    2. Hernan M. A & Brumback B. & Robins J. M, 2001. "Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 440-448, June.
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    Cited by:

    1. Brent A. Johnson & Heather Ribaudo & Roy M. Gulick & Joseph J. Eron, 2013. "Modeling Clinical Endpoints as a Function of Time of Switch to Second‐Line ART with Incomplete Data on Switching Times," Biometrics, The International Biometric Society, vol. 69(3), pages 732-740, September.
    2. Hao Sun & Ashkan Ertefaie & Brent A. Johnson, 2022. "Estimating mean potential outcome under adaptive treatment length strategies in continuous time," Biometrics, The International Biometric Society, vol. 78(4), pages 1503-1514, December.
    3. Xin Lu & Brent A. Johnson, 2017. "Direct estimation for adaptive treatment length policies: Methods and application to evaluating the effect of delayed PEG insertion," Biometrics, The International Biometric Society, vol. 73(3), pages 981-989, September.
    4. Liangyuan Hu & Joseph W. Hogan & Ann W. Mwangi & Abraham Siika, 2018. "Modeling the causal effect of treatment initiation time on survival: Application to HIV/TB co†infection," Biometrics, The International Biometric Society, vol. 74(2), pages 703-713, June.
    5. Andrew J. Spieker & Emily M. Ko & Jason A. Roy & Nandita Mitra, 2020. "Nested g‐computation: a causal approach to analysis of censored medical costs in the presence of time‐varying treatment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1189-1208, November.
    6. Shu Yang & Anastasios A. Tsiatis & Michael Blazing, 2018. "Modeling survival distribution as a function of time to treatment discontinuation: A dynamic treatment regime approach," Biometrics, The International Biometric Society, vol. 74(3), pages 900-909, September.
    7. Anastasios A. Tsiatis & Marie Davidian, 2005. "Discussion on "Statistical Issues Arising in the Women's Health Initiative"," Biometrics, The International Biometric Society, vol. 61(4), pages 933-935, December.
    8. Bo Lu & Zhenchao Qian & Anna Cunningham & Chih-Lin Li, 2012. "Estimating the Effect of Premarital Cohabitation on Timing of Marital Disruption," Sociological Methods & Research, , vol. 41(3), pages 440-466, August.
    9. Johnson, Brent A. & Boos, Dennis D., 2005. "A note on the use of kernel functions in weighted estimators," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 345-355, May.
    10. Sun Hao & Ertefaie Ashkan & Lu Xin & Johnson Brent A., 2020. "Improved Doubly Robust Estimation in Marginal Mean Models for Dynamic Regimes," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 300-314, January.

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