Abstract
Cohort studies are routinely conducted to learn about the incidence or progression rates of chronic diseases. The illness-death model offers a natural framework for joint consideration of non-fatal events in the semi-competing risks setting. We consider the design of prospective cohort studies where the goal is to estimate the effect of a marker on the risk of a non-fatal event which is subject to interval-censoring due to an intermittent observation scheme. The sample size is shown to depend on the effect of interest, the number of assessments, and the duration of follow-up. Minimum-cost designs are also developed to account for the different costs of recruitment and follow-up examination. We also consider the setting where the event status of individuals is observed subject to misclassification; the consequent need to increase the sample size to account for this error is illustrated through asymptotic calculations.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Nathalie C. Moon http://orcid.org/0000-0001-7789-205X
Leilei Zeng http://orcid.org/0000-0002-2336-7249
Richard J. Cook http://orcid.org/0000-0002-1414-4908
Additional information
Funding
Notes on contributors
Nathalie C. Moon
Nathalie C. Moon is an Assistant Professor, Teaching Stream in the Department of Statistical Sciences at the University of Toronto
Leilei Zeng
Leilei Zeng is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo.
Richard J. Cook
Richard J. Cook is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo and a Faculty Research Chair.