Information in the sample covariate distribution in prevalent cohorts

Methods of estimation and inference about survival distributions based on length‐biased samples are well‐established. Comparatively little attention has been given to the assessment of covariate effects in the context of length‐biased samples, but prevalent cohort studies often have this objective....

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Bibliographic Details
Published in:Statistics in medicine 2011-05, Vol.30 (12), p.1397-1409
Main Authors: Cook, Richard J., Bergeron, Pierre-Jérôme
Format: Article
Language:English
Subjects:
Age of Onset
Aged
Aged, 80 and over
aging
Alzheimer Disease - mortality
asymptotic efficiency
Asymptotic methods
Canada
Cohort Studies
covariate distribution
dementia disorders
Effects
Estimating techniques
Estimation bias
Female
Humans
Incidence
Information
left truncation
length-biased sampling
Male
Models, Statistical
Mortality
prevalent cohort
right censoring
Risk factors
survival
Survival Analysis
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Summary:Methods of estimation and inference about survival distributions based on length‐biased samples are well‐established. Comparatively little attention has been given to the assessment of covariate effects in the context of length‐biased samples, but prevalent cohort studies often have this objective. We show that, like the survival distribution, the covariate distribution from a prevalent cohort study is length‐biased, and that this distribution may contain parametric information about covariate effects on the survival time. As a result, a likelihood based on the joint distribution of the survival time and the covariates yields estimates of covariate effects which are at least as efficient as estimates arising from a traditional likelihood which conditions on covariate values in the length‐biased sample. We also investigate the empirical bias of estimators arising from a joint likelihood when the population covariate distribution is misspecified. The asymptotic relative efficiencies and empirical biases under model misspecification are assessed for both proportional hazards and accelerated failure time models. The various methods considered are applied in an illustrative analysis of risk factors for death following onset of dementia using data collected in the Canadian Study of Health and Aging. Copyright © 2011 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.4180