@article {6739,
	title = {Time to diagnosis: accounting for differential follow-up times in cohort studies.},
	journal = {Communications in Statistics-Simulation and Computation},
	volume = {44},
	year = {2015},
	month = {2015},
	chapter = {247},
	abstract = {Cox regression is widely used to analyze discrete survival time data. Differential endpoint follow-up across sub-cohorts where distribution of a covariate varies may cause typical estimators to be biased or inefficient. We demonstrate that with Cardiovascular Health Study data for incident type 2 diabetes. Two cohorts with extremely different race distribution have differential follow-up for fasting glucose levels. We study various scenarios of Cox regression. We suggest an alternative approach, Poisson generalized estimating equations with an offset to accommodate the differential follow-up. We use simulations to contrast the methods.},
	keywords = {62N01, Covariate-dependent follow-up, Discrete survival data, Multi-cohort studies, Primary 62N02, Secondary 62H12},
	author = {B{\r u}zkov{\'a}, Petra},
	editor = {Lumley, Thomas}
}
