Maximum Likelihood Estimations and EM Algorithms with Length-biased Data.

ABSTRACT: Length-biased sampling has been well recognized in economics, industrial reliability, etiology applications, epidemiological, genetic and cancer screening studies. Length-biased right-censored data have a unique data structure different from traditional survival data. The nonparametric and semiparametric estimations and inference methods for traditional survival data are not directly applicable for length-biased right-censored data. We propose new expectation-maximization algorithms for estimations based on full likelihoods involving infinite dimensional parameters under three settings for length-biased data: estimating nonparametric distribution function, estimating nonparametric hazard function under an increasing failure rate constraint, and jointly estimating baseline hazards function

SUBMITTER: Qin J 

PROVIDER: S-EPMC3273908 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature