Online Program Home
My Program

Abstract Details

Activity Number: 414 - Advances in Estimation Methods
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #328312
Title: Doubly Robust Estimation and Causal Inference for Recurrent Event Data
Author(s): Chien-Lin Mark Su* and Russell Steele and Ian Shrier
Companies: McGill University and McGill University and McGill University
Keywords: Average causal effect; Confounder; Multiplicative rate model; Nelson-Aalen estimator; Recurrent events

Recurrent events are frequently observed in many biomedical longitudinal studies. The interest of this paper is to estimate the average causal effects for recurrent event data in the presence of confounders. We propose a doubly robust estimator which combines the weighted Nelson-Aalen estmator and regression estimator based on an assumed semiparametic multiplicative rate model for recurrent event data. The proposed estimators are shown to be consistent and asymptotically normal. In addition, a model diagnostic plot of residuals is presented to assess the adequacy of the semiparametric model. The finite sample behavior of the proposed estimators is evaluated through simulation studies. The proposed methodologies are illustrated via an injury database for circus artists.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program