On the Analysis of Grouped Survival Data Using Cumulative Occurrence/Exposure Rates

Abstract

One may estimate a conditional hazard function from grouped (and possibly censored) survival data by the time and covariate specific occurrence/exposure rate. Asymptotic results for cumulative versions of this estimator are developed, utilizing the general frame-work of counting processes. In particular, a grouped data based goodness of fit test for Cox's proportional hazard model is given. Various constraints on the asymptotic behavior of the widths of the calendar periods and covariate strata employed in grouping the data are needed to prove the results. Actual performance of the estimators and test statistics is evaluated by Monte Carlo methods.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1991
Accession Number
ADA238219

Entities

People

  • Ian W. Mckeague
  • Mei-jie Zhang

Organizations

  • Florida State University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Data Analysis
  • Data Mining
  • Data Science
  • Estimators
  • Goodness Of Fit Tests
  • Information Science
  • Military Research
  • Monte Carlo Method
  • Normality
  • Nuclear Bombs
  • Regression Analysis
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Time Intervals

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.