A semi-parametric weighted likelihood approach for regression analysis of bivariate interval-censored outcomes from case-cohort studies

Yichen Lou, Peijie Wang () and Jianguo Sun
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Yichen Lou: Jilin University
Peijie Wang: Jilin University
Jianguo Sun: University of Missouri

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2023, vol. 29, issue 3, No 7, 628-653

Abstract: Abstract The case-cohort design was developed to reduce costs when disease incidence is low and covariates are difficult to obtain. However, most of the existing methods are for right-censored data and there exists only limited research on interval-censored data, especially on regression analysis of bivariate interval-censored data. Interval-censored failure time data frequently occur in many areas and a large literature on their analyses has been established. In this paper, we discuss the situation of bivariate interval-censored data arising from case-cohort studies. For the problem, a class of semiparametric transformation frailty models is presented and for inference, a sieve weighted likelihood approach is developed. The large sample properties, including the consistency of the proposed estimators and the asymptotic normality of the regression parameter estimators, are established. Moreover, a simulation is conducted to assess the finite sample performance of the proposed method and suggests that it performs well in practice.

Keywords: Bivariate interval-censored data; Case-cohort design; Frailty; Weighted likelihood (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10985-023-09593-9

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