Parametric models for response-biased sampling

• 成果类型: Article
• 署名作者: Chen, KN
• 署名单位: Hong Kong University of Science & Technology
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/1467-9868.00312
• 发表日期: 2001
• 页码: 775-789
• 关键词: case-cohort; regression

摘要

Suppose that subjects in a population follow the model f (y*\x*; theta) where y* denotes a response, x* denotes a vector of covariates and theta is the parameter to be estimated. We consider response-biased sampling, in which a subject is observed with a probability which is a function of its response. Such response-biased sampling frequently occurs in econometrics, epidemiology and survey sampling. The semiparametric maximum likelihood estimate of theta is derived, along with its asymptotic normality, efficiency and variance estimates. The estimate proposed can be used as a maximum partial likelihood estimate in stratified response-selective sampling. Some computation algorithms are also provided.