Semiparametric model-based inference in the presence of missing responses

• 成果类型: Article
• 署名作者: Wang, Qihua; Dai, Pengjie
• 署名单位: Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asn032
• 发表日期: 2008
• 页码: 721734
• 关键词: likelihood-based inference; multiple imputation; mean functionals

摘要

We consider a semiparametric model that parameterizes the conditional density of the response, given covariates, but allows the marginal distribution of the covariates to be completely arbitrary. Responses may be missing. A likelihood-based imputation estimator and a semi-empirical-likelihood-based estimator for the parameter vector describing the conditional density are defined and proved to be asymptotically normal. Semi-empirical loglikelihood functions for the parameter vector and the response mean are derived. It is shown that the two semi-empirical loglikelihood functions are distributed asymptotically as weighted chi(2) and scaled chi(2), respectively.