Statistics Seminar
| Date/Time: | Monday, 28 Sep 2015 from 4:10 pm to 5:00 pm |
|---|---|
| Location: | Snedecor 3105 |
| Cost: | Free |
| URL: | www.stat.iastate.edu |
| Phone: | 515-294-3440 |
| Channel: | College of Liberal Arts and Sciences |
| Categories: | Lectures |
| Actions: | Download iCal/vCal | Email Reminder |
An important goal in clinical and statistical research is estimating the distribution for clustered failure times, which have a natural intra-class dependency and are subject to censoring. We propose to handle these inherent challenges with a novel approach that does not impose restrictive modeling or distributional assumptions. Rather, using a logit transformation, we relate the distribution for clustered failure times to covariates and a random, subject-specic eect such that the covariates are modeled with unknown functional forms, and the random eect is distribution-free and potentially correlated with the covariates. Over a range of time points, the model is shown to be reminiscent of an additive logistic mixed eect model. Such a structure allows us to handle censoring via pseudo-value regression and to develop semiparametric techniques that completely factor out the unknown random eect. We show both theoretically and empirically that the resulting estimator is consistent for any choice of random eect distribution and for any dependency structure between the random eect and covariates. Lastly, we illustrate the method's utility in an application to the Cooperative Huntington's Observational Research Trial data, where our method provides new insights into differences between motor and cognitive impairment event times in subjects at risk for Huntington's disease.