Goodness-of-Fit Tests for Additive Hazards and Proportional Hazards Models

Abstract

Additive hazards and proportional hazards regression models used in the analysis of censored survival data can give substantially different results. For instance, in connection with a study of cancer mortality among Japanese atomic bomb survivors, Muirhead and Darby (1987) have noted that the two models give substantially different estimates of the age-specific probability that an individual will develop radiation induced cancer. Muirhead and Darby introduced a generalized parametric model which contains parametric additive hazards and proportional hazards models as special cases. The goodness-of-fit of each model is then obtained by comparing with the best fitting model within the generalized family, allowing the two special models to be treated on an equal footing. The purpose of this paper is to develop formal goodness-of-fit tests for the models of Aalen and Cox in which each model is compared on an equal footing with the best fitting fully nonparametric model.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1988
Accession Number
ADA202440

Entities

People

  • Ian W. Mckeague
  • Klaus J. Utikal

Organizations

  • Florida State University

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Convergence
  • Covariance
  • Data Science
  • Frequency
  • Goodness Of Fit Tests
  • Information Science
  • Integrals
  • Mathematics
  • Military Research
  • Nuclear Bombs
  • Radiation
  • Regression Analysis
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Universities
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Statistical inference.