The aim of this two year project is to develop and test new statistical methods for the analysis of prevalence case-control survival data. Prevalence case-control survival studies may be a powerful approach to study time to onset of disease, and to evaluate the association between risk factors and probability of developing the disease. In many cases, prevalence case-control survival studies are more efficient than incidence case-control or prospective cohort studies. Unfortunately, no statistical methods are currently available for an efficient analysis of data from prevalence case-control survival studies.
The specific aims of this project are: 1) To extend methods for the analysis of data from prevalence case-control studies developed in the setting of the one-sample problem (no covariates included in the analysis) to the setting of the two-sample problem, i.e., to develop methods for estimating and comparing survival distributions for two different risk groups; 2) To use the methods developed in Aim (1) to analyze survival data from a prevalence case-control sample of patients with adenomatous polyps (adenomas); 3) To develop regression methods for the analysis of prevalence case-control survival data; 4) To develop user-friendly software for the analysis of survival data from prevalence case-control studies. Development of the new methods is based on an extension of the usual approach to the analysis of case-control data of embedding the case-control likelihood into a prospective likelihood, and on methods of analysis of right truncated survival data. The methodological as well as epidemiological relevance of this proposal is that it provides appropriate and efficient methods of analysis of data from prevalence case-control survival data.
| Bagiella, Emilia (2006) Estimating and comparing the distribution of onset of disease from prevalence case-control data. Biometrics 62:54-60 |
