具有协变量的不完全数据的选择模型和模式混合模型。

Selection models and pattern-mixture models for incomplete data with covariates.

作者信息

Michiels B, Molenberghs G, Lipsitz S R

机构信息

Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium.

出版信息

Biometrics. 1999 Sep;55(3):978-83. doi: 10.1111/j.0006-341x.1999.00978.x.

DOI:10.1111/j.0006-341x.1999.00978.x

PMID:11315038

Abstract

Most models for incomplete data are formulated within the selection model framework. This paper studies similarities and differences of modeling incomplete data within both selection and pattern-mixture settings. The focus is on missing at random mechanisms and on categorical data. Point and interval estimation is discussed. A comparison of both approaches is done on side effects in a psychiatric study.

摘要

大多数不完全数据模型是在选择模型框架内构建的。本文研究了在选择和模式混合设置下对不完全数据建模的异同。重点在于随机缺失机制和分类数据。讨论了点估计和区间估计。在一项精神病学研究中，对两种方法在副作用方面进行了比较。