title: Estimation of state occupancy probabilities in multistate models with dependent intermittent observation, with application to HIV viral rebounds.
abstract: In follow-up studies on chronic disease cohorts, individuals are often observed at irregular visit times that may be related to their previous disease history and other factors. This can produce bias in standard methods of estimation. Working in the context of multistate models, we consider a method of nonparametric estimation for state occupancy probabilities that adjusts for dependent follow-up through the use of inverse-intensity-of-visit weighted estimating functions and smoothing. The methodology is applied to the estimation of viral rebound probabilities in the Canadian Observational Cohort on HIV-positive persons. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute, 60 Murray Street, Toronto, M5T 3L9, ON, Canada.
authors.forename: N
authors.initials: N
authors.lastname: Nazeri Rad
authors.affiliation: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, N2L 3G1, ON, Canada.
authors.forename: J F
authors.initials: JF
authors.lastname: Lawless
mesh_terms: D002170:Canada / Q000453:epidemiology; D005500:Follow-Up Studies; D015658:HIV Infections / Q000453:epidemiology / Q000821:virology*; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D064887:Observational Studies as Topic; D011336:Probability; D013997:Time Factors; D019562:Viral Load / Q000706:statistics & numerical data*
keywords: dependent follow-up; intermittent observation; multistate models; nonparametric estimation; state occupancy probabilities