Abstract
In this paper, we consider clustered right-censored time-to-event data. Such data can be analysed either using a marginal model if one is interested in population effects or using so-called frailty models if one is interested in covariate effects on the individual level and in estimation of correlation. The Cox frailty model has been studied extensively in the last decade or so and estimation techniques and large sample results are now available. It is, however, difficult to deal with time-changing covariate effects when using the Cox model. An appealing alternative model is the Aalen additive hazards model, in which it is easy to work with time dynamics. In this paper, we describe an innovative approach to estimation in the Aalen additive gamma frailty hazards model. We give the large sample properties of the estimators and investigate their small sample properties by Monte Carlo simulation. A real example is provided for illustration.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Biometrika |
| Vol/bind | 98 |
| Udgave nummer | 4 |
| Sider (fra-til) | 831-843 |
| Antal sider | 13 |
| ISSN | 0006-3444 |
| DOI | |
| Status | Udgivet - dec. 2011 |