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Activity Number: 402 - Statistical Methods for New Challenges in Lifetime/Complex Data
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2020 : 1:00 PM to 2:50 PM
Sponsor: Lifetime Data Science Section
Abstract #309687
Title: Simultaneous Monitoring for Regression Coefficients and Baseline Hazard Profile in Cox Modeling of Time-to-Event Data
Author(s): Jun Yan* and Yishu Xue and Elizabeth Schifano
Companies: University of Connecticut and University of Connecticut and University of Connecticut
Keywords: multivariate quality control; profile control; survival analysis

The Cox model is the most popular tool for analyzing time-to-event data. The nonparametric baseline hazard function can be as important as the regression coefficients in practice, especially when prediction is needed. In the context of stochastic process control, we propose a simultaneous monitoring method that combines a multivariate control chart for the regression coefficients and a profile control chart for the cumulative baseline hazard function, that allows for data blocks of possibly different censoring rates and sample sizes. The method can detect changes in either the parametric or the nonparametric part of the Cox model. In simulation studies, the proposed method maintains its size and has substantial power in detecting changes in either part of the Cox model. An application in lymphoma survival analysis in which patients were enrolled by two month intervals in the Surveillance, Epidemiology, and End Results program identifies data blocks with structural model changes.

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

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