A dynamic adaptation of the propensity score adjustment for effectiveness analyses of ordinal doses of treatment

Authors

  • Andrew C. Leon,

    Corresponding author
    1. Cornell University Medical College, Department of Psychiatry, Box 140, 525 East 68th Street, New York, NY 10021, U.S.A.
    • Cornell University Medical College, Department of Psychiatry, Box 140, 525 East 68th Street, New York, NY 10021, U.S.A.
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  • Timothy I. Mueller,

    1. Brown University, Department of Psychiatry and Human Behavior, Butler Hospital, Duncan Building, 345 Blackstone Boulevard, Providence, RI 02906, U.S.A.
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  • David A. Solomon,

    1. Brown University, Department of Psychiatry and Human Behavior, Rhode Island Hospital, Department of Psychiatry, 593 Eddy Street, Providence, RI 02903, U.S.A.
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  • Martin B. Keller

    1. Brown University, Department of Psychiatry and Human Behavior, Rhode Island Hospital, Department of Psychiatry, 593 Eddy Street, Providence, RI 02903, U.S.A.
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Abstract

The propensity score adjustment is a method to reduce bias in observational studies. We propose a strategy that involves a novel combination of three data analytic techniques, which adapts the propensity adjustment for additional perturbations of longitudinal, observational studies. First, ordinal logistic regression examines propensity for ordinal doses of treatment. Second, a mixed-model approach incorporates the multiple treatment trials and multiple episodes that are characteristic of chronically ill subjects. Finally, a mixed-effects grouped-time survival model incorporates the propensity score in treatment effectiveness analyses. The strategy that is applied here to an observational study of affective illness can also be used to evaluate the effectiveness of treatments for other chronic illnesses. Copyright © 2001 John Wiley & Sons, Ltd.

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