Zeng, LeileiCook, Richard J.Lee, Jooyoung2020-03-112020-03-112020-02-20https://doi.org/10.1002/sim.8411http://hdl.handle.net/10012/15692This is the peer reviewed version of the following article: Leilei Zeng, Richard J. Cook and Jooyoung Lee, Multistate analysis from cross-sectional and auxiliary samples. Statistics in Medicine (2019), 39(4): 387–408 which has been published in final form at https://doi.org/10.1002/sim.8411.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.enauxiliary datacross-sectional sampleintensity functionMarkov modelmultistage disease processArticle