An Approach to Solving the Problem of Missing Data: Identifying and Dealing with Mechanisms Adequately

被引：3
|
作者：
Cho, A. [1 ]
Leonhart, R. [1 ]
机构：
[1] Univ Freiburg, Inst Psychol, D-79106 Freiburg, Germany
来源：
REHABILITATION | 2013年 / 52卷 / 04期
关键词：
missing data; missing data mechanisms; MCAR-test; classic procedures; imputation procedures; multiple imputation; SAMPLE SELECTION; VARIABLES;
D O I：
10.1055/s-0032-1327588
中图分类号：
R49 [康复医学];
学科分类号：
100215 ;
摘要：
Being confronted with missing data, the most important step is the knowledge of the underlying mechanism. In consequence of this, modern missing data techniques in contrast to past techniques are presented and compared, which can deal with more common situations. Finally, concrete instructions for the correct treatment of missing data are given.
引用
收藏
页码：274 / 280
页数：7
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