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Activity Number: 524 - Contributed Poster Presentations: Lifetime Data Science Section
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Lifetime Data Science Section
Abstract #304533
Title: Infinite Parameter Estimates in Proportional Hazards Regression
Author(s): John E Kolassa* and Juan Zhang
Companies: Rutgers, the State University of New Jersey and Allergan Pharmaceuticals
Keywords: Proportional Hazards; Survival Analysis; Conditional Inference

Proportional hazards regression shares the possibility of infinite parameter estimation with logistic and multinomial regression. This poster demonstrates how to perform approximate conditional inference on finite components of the proportional hazards regression model in the presence of infinite estimates for nuisance parameters, by employing optimization techniques to reduce the data set to one yielding conditional inference approximating that of the desired regression model.

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

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