Conditional regression models for transient state survival analysis.

Abstract:

:Survival models are important tools for the analysis of data when a disease event occurs in 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 adaptations 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.

journal_name

Am J Epidemiol

authors

Abbott RD,Carroll RJ

doi

10.1093/oxfordjournals.aje.a114293

subject

Has Abstract

pub_date

1986-04-01 00:00:00

pages

728-35

issue

4

eissn

0002-9262

issn

1476-6256

journal_volume

123

pub_type

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