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ERIC Number: EJ1086430
Record Type: Journal
Publication Date: 2016
Pages: 17
Abstractor: As Provided
ISSN: ISSN-0022-0973
Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance
Finch, W. Holmes
Journal of Experimental Education, v84 n2 p356-372 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in the context of a MANOVA, with the typical default for dealing with missing data: listwise deletion. When data are missing at random, the new methods maintained the nominal Type I error rate and had power comparable to the complete data condition. When 40% of the data were missing completely at random, the Type I error rates for the new methods were inflated, but not for lower percents.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Wechsler Intelligence Scale for Children
Grant or Contract Numbers: N/A