Estimation in the General Multiplicative Model for Survival.

Abstract

The general multiplicative model represents the hazard function as the product of an 'underlying hazard rate, gamma (t), of unspecified form and a certain function of known form, g(z; beta), where z is a vector of concomitant variables, and Beta is a vector of unknown parameters. Assuming that gamma (t) can be approximated by a constant between any two consecutive failures, the general forms of likelihood function are derived. The likelihood utilizes the available information on the time of exposure to risk of each individual (until failure or withdrawal). Special cases, when the z's do not depend on t are discussed in some detail. Multiple failures are handled in a simple manner - no ordering of failures is required. Estimation of empirical survival function when there are no covariates is discussed. An example using heart transplant data, is given (for illustrative purpose only).

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1978
Accession Number
ADA059998

Entities

People

  • Norman L. Johnson
  • Regina C. Elandt-johnson

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Biometrics
  • Biostatistics
  • Blood Groups
  • Clinical Trials
  • Data Science
  • Estimators
  • Health
  • Information Science
  • Intervals
  • Maximum Likelihood Estimation
  • North Carolina
  • Observation
  • Public Health
  • Statistics
  • Survival
  • Transplants

Fields of Study

  • Mathematics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Cardiovascular Physiology
  • Regression Analysis.

Technology Areas

  • Biotechnology