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Activity Number:
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330
- Advances in Time-to-Event and Survival Methods
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Type:
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Contributed
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Date/Time:
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Tuesday, August 9, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #322482
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Title:
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General Regression Model for the Marginal Mean of a Recurrent Event with Competing Terminal Events
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Author(s):
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Anna Bellach*
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Companies:
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National Institute of Health
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Keywords:
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recurrent events and competing terminal events;
semiparametric models;
marginal mean
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Abstract:
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Regression modeling of recurrent event data with competing terminal events is of great importance for clinical trials. We propose a general regression model targeting directly the marginal mean of the recurrent event. The novel approach captures a large class of semiparametric regression models and accommodates external time-dependent covariate effects on the marginal mean. We establish the consistency and asymptotic normality of the estimators and provide a sandwich estimator for the variance. In simulation studies, we demonstrate a solid performance of the proposed estimators under independent right censoring. An application to cancer data is provided to demonstrate the practical utility of the model.
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Authors who are presenting talks have a * after their name.
