Multistate analysis from cross-sectional and auxiliary samplesopen access
- Authors
- Zeng, L.; Cook, R.J.; Lee, J.
- Issue Date
- 2020
- Publisher
- John Wiley and Sons Ltd
- Keywords
- auxiliary data; cross-sectional sample; intensity function; Markov model; multistage disease process
- Citation
- Statistics in Medicine, v.39, no.4, pp 387 - 408
- Pages
- 22
- Journal Title
- Statistics in Medicine
- Volume
- 39
- Number
- 4
- Start Page
- 387
- End Page
- 408
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/63462
- DOI
- 10.1002/sim.8411
- ISSN
- 0277-6715
1097-0258
- Abstract
- 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. © 2019 John Wiley & Sons, Ltd.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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