Semiparametric analysis of survival data with left truncation and right censoring

Pao-sheng Shen

Computational Statistics & Data Analysis, 2009, vol. 53, issue 12, 4417-4432

Abstract: Let T, C and V denote the lifetime, censoring and truncation variables, respectively. Assume that (C,V) is independent of T and P(C>=V)=1. Let F, Q and G denote the common distribution functions of T, C and V, respectively. For left-truncated and right-censored (LTRC) data, one can observe nothing if T =V. For LTRC data, the truncation product-limit estimate is the maximum likelihood estimate (MLE) for nonparametric models. If the distribution of V is parameterized as G(x;[theta]) and the distributions of T and C are left unspecified, the product-limit estimate is not the MLE for this semiparametric model. In this article, for LTRC data, two semiparametric estimates are proposed for the semiparametric model. A simulation study is conducted to compare the performances of the two semiparametric estimators against that of . The proposed semiparametric method is applied to a Channing House data.

Date: 2009
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