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Time to diagnosis: accounting for differential follow-up times in cohort studies.
Tuesday,2015-06-16 12:14 America/Los_Angeles — zdrager
| Title | Time to diagnosis: accounting for differential follow-up times in cohort studies. |
| Publication Type | Journal Article |
| Year of Publication | 2015 |
| Authors | Bůzková, P |
| Secondary Authors | Lumley, T |
| Journal | Communications in Statistics-Simulation and Computation |
| Volume | 44 |
| Issue | 1 |
| Start Page | 247 |
| Date Published | 2015 |
| Keywords | 62N01, Covariate-dependent follow-up, Discrete survival data, Multi-cohort studies, Primary 62N02, Secondary 62H12 |
| 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. |
| Alternate Journal | Communications in Statistics-Simulation and Computation |
ePub date:
14/07