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