Conditional Regression Models for Transient State Survival Analysis.

Abstract

Survival models are important tools for the analysis of data when a disease event occurs with time and subjects are lost to follow-up. Many models, however, can also be adapted for use when an event is characterized by transitions through intermediate states of disease with increasing severity. In this presentation, such an adaptation will be demonstrated for a class of conditional regression models for the analysis of transient state events occurring among grouped event times. The type of conditioning that will be described is useful in providing comparisons of specific disease states and an assessment of transition dependent risk factor effects. An example will be given based on the Framingham Heart Study. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1984
Accession Number
ADA147872

Entities

People

  • R. D. Abbott
  • Raymond J. Carroll

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Air Force
  • Analysis Of Variance
  • Cardiovascular Physiological Phenomena
  • Cholesterol
  • Coefficients
  • Data Analysis
  • Data Mining
  • Data Science
  • Death
  • Diseases And Disorders
  • Health
  • Heart Diseases
  • Information Science
  • Myocardial Ischemia
  • Risk Factors
  • Statistics
  • Time Intervals

Fields of Study

  • Mathematics

Readers

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  • Thermal Physics or Thermal Science.