Cancer Institute A national cancer institute
designated cancer center

Philip W. Lavori

Publication Details

  • Using inverse weighting and predictive inference to estimate the effects of time-varying treatments on the discrete-time hazard STATISTICS IN MEDICINE Dawson, R., Lavori, P. W. 2002; 21 (12): 1641-1661


    We estimate the effects of non-randomized time-varying treatments on the discrete-time hazard, using inverse weighting. We consider the special monotone pattern of treatment that develops over time as subjects permanently discontinue an initial treatment, and assume that treatment selection is sequentially ignorable. We use a propensity score in the hazard model to reduce the potential for finite-sample bias due to inverse weighting. When the number of subjects who discontinue treatment at any given time is small, we impose scientific restrictions on the potentially observable discontinuation hazards to improve efficiency. We use predictive inference to account for the correlation of the potential hazards, when comparing outcomes under different durations of initial treatment.

    View details for DOI 10.1002/sim.1111

    View details for Web of Science ID 000176360000001

    View details for PubMedID 12111903

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