@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} }