作者
Craig K Enders, Amanda N Baraldi, Heining Cham
发表日期
2014/3
期刊
Psychological methods
卷号
19
期号
1
页码范围
39
出版商
American Psychological Association
简介
The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (eg, a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline …
学术搜索中的文章
CK Enders, AN Baraldi, H Cham - Psychological methods, 2014