Sequential Analysis of the Proportional Hazards Model.

Abstract

For the proportional hazards model of survival analysis, an appropriate large sample theory is developed for cases of staggered entry and sequential analysis. The principal techniques involve an approximation of the score process by a suitable martingale and a random rescaling of time based on the observed Fisher information. As a result we show that the maximum partial likelihood estimator behaves asymptotically like Brownian motion. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1982
Accession Number
ADA119375

Entities

People

  • David Siegmund
  • T. Sellke

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Brownian Motion
  • Clinical Trials
  • Data Science
  • Estimators
  • Information Science
  • Integrals
  • Military Research
  • New York
  • Notation
  • Probability
  • Random Variables
  • Sequential Analysis
  • Statistics
  • Survival
  • United States
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.