Conditional regression models for transient state survival analysis. Academic Article

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.

authors

• Carroll, Raymond

published proceedings

• Am J Epidemiol

author list (cited authors)

• Abbott, R. D., & Carroll, R. J.

citation count

• 3

complete list of authors

• Abbott, RD||Carroll, RJ

publication date

• April 1986

publisher

• Oxford University Press (OUP)  Publisher

published in

• American Journal of Epidemiology  Journal

keywords

• Adult
• Blood Pressure
• Cholesterol
• Coronary Disease
• Epidemiology
• Humans
• Male
• Middle Aged
• Models, Biological
• Prognosis
• Regression Analysis
• Risk
• Smoking
• Statistics As Topic

PubMed Central ID

• 3953550

Digital Object Identifier (DOI)

• 10.1093/oxfordjournals.aje.a114293

start page

• 728

end page

• 735

volume

• 123

issue

• 4

URL

• http%3A%2F%2Fdx.doi.org%2F10.1093%2Foxfordjournals.aje.a114293