| Literature DB >> 7766796 |
Abstract
In typical nest survival studies, the observed sample of nests is usually biased by left-truncation (i.e., only active nests enter the study); additionally the failure data may be doubly censored, because the exact dates of nest initiation and failure are uncertain. We present a general bivariate contingency table approach for analyzing such data. We use weakly structured step spline hazard models, which avoid estimability problems encountered in a strictly nonparametric approach, yet still permit flexibility. Our method eliminates a potential source of bias noted by Heisey and Nordheim (1990, Biometrics 46, 855-862) in the nest survival method of Pollock and Cornelius (1988, Biometrics 44, 397-404). We compare our approach to related techniques developed for estimating the incubation distribution of AIDS.Entities:
Mesh:
Year: 1995 PMID: 7766796
Source DB: PubMed Journal: Biometrics ISSN: 0006-341X Impact factor: 2.571