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ERIC Number: EJ998538
Record Type: Journal
Publication Date: 2012
Pages: 14
Abstractor: As Provided
ISSN: ISSN-1554-7558
Strategies for Handling Missing Data with Maximum Likelihood Estimation in Career and Technical Education Research
Lee, In Heok
Career and Technical Education Research, v37 n3 p297-310 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of reporting the presence of and methods for treating missing data and has encouraged implementing state-of-the-art missing data methods such as multiple imputation and maximum likelihood estimation (see Baraldi & Enders, 2010; Enders, 2006b; Schafer & Graham, 2002; Schlomer, Bauman, & Card, 2010). This article provides a brief overview of maximum likelihood methods for handling missing data, which have several advantages over multiple imputation methods. Additionally, practical strategies for implementing and reporting the treatment of missing data using maximum likelihood methods are discussed. (Contains 3 tables and 2 figures.)
Association for Career and Technical Education Research. Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Adult Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A