Multistate analysis from cross-sectional and auxiliary samples

被引：1

作者：

Zeng, Leilei ^{[1
]}

Cook, Richard J. ^{[1
]}

Lee, Jooyoung ^{[1
]}

机构：

[1] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON N2L 3G1, Canada

来源：

STATISTICS IN MEDICINE | 2020年 / 39卷 / 04期

基金：

加拿大健康研究院; 加拿大自然科学与工程研究理事会;

关键词：

auxiliary data; cross-sectional sample; intensity function; Markov model; multistage disease process; PSORIATIC-ARTHRITIS; NONPARAMETRIC-ESTIMATION; ODDS RATIO; PREVALENCE; HISTORY; MODELS; COHORT; DEATH; EPIDEMIOLOGY; PROGRESSION;

D O I：

10.1002/sim.8411

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Epidemiological studies routinely involve cross-sectional sampling of a population comprised of individuals progressing through life history processes. We consider features of a cross-sectional sample in terms of the intensity functions of a progressive multistate disease process under stationarity assumptions. The limiting values of estimators for regression coefficients in naive logistic regression models are studied, and simulations confirm the key asymptotic results that are relevant in finite samples. We also consider the need for and the use of data from auxiliary samples, which enable one to fit the full multistate life history process. We conclude with an application to data from a national cross-sectional sample assessing marker effects on psoriatic arthritis among individuals with psoriasis.

引用

页码：387 / 408

页数：22

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