A discussion of 'statistical inference for nonignorable missing data problems: a selective review'by Niansheng Tang and Yuanyuan Ju
K Morikawa, JK Kim - Statistical Theory and Related Fields, 2018 - Taylor & Francis
Statistical Theory and Related Fields, 2018•Taylor & Francis
We congratulate Tang and Ju for their refined review paper on the recent statistical inference
of nonignorable missing data. This paper covers various topics in missing data analysis
including semiparametric estimation, Bayesian inference, structural equation modelling,
sensitivity analysis and model selection, so that it fills the gap between complete and
missing data analysis. We have a comment on the semiparametric estimation of mean
functionals. With known γ, they used 'n− 1
of nonignorable missing data. This paper covers various topics in missing data analysis
including semiparametric estimation, Bayesian inference, structural equation modelling,
sensitivity analysis and model selection, so that it fills the gap between complete and
missing data analysis. We have a comment on the semiparametric estimation of mean
functionals. With known γ, they used 'n− 1
We congratulate Tang and Ju for their refined review paper on the recent statistical inference of nonignorable missing data. This paper covers various topics in missing data analysis including semiparametric estimation, Bayesian inference, structural equation modelling, sensitivity analysis and model selection, so that it fills the gap between complete and missing data analysis. We have a comment on the semiparametric estimation of mean functionals. With known γ, they used ‘n− 1
Taylor & Francis Online以上显示的是最相近的搜索结果。 查看全部搜索结果