Dealing with missing data: Part II

被引：70

作者：

Walczak, B ^{[1
]}

Massart, DL ^{[1
]}

机构：

[1] Fabi VUB, ChemoAC, B-1090 Brussels, Belgium

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2001年 / 58卷 / 01期

关键词：

maximum likelihood; multiple imputation; missing data;

D O I：

10.1016/S0169-7439(01)00132-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The main concepts of the maximum likelihood (ML) approach in dealing with missing data are introduced and simple numerical examples of the application of ML are presented. Differences between ML and other techniques of treating missing data are illustrated. The idea of multiple imputation (MI) approach is presented and illustrated as well. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：29 / 42

页数：14

共 25 条

[1] MISSING OBSERVATIONS IN MULTIVARIATE STATISTICS .3. LARGE SAMPLE ANALYSIS OF SIMPLE LINEAR REGRESSION [J].