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ERIC Number: EJ800334
Record Type: Journal
Publication Date: 2008-Jul
Pages: 20
Abstractor: As Provided
Reference Count: 25
ISSN: ISSN-0895-7347
Using Structural Equation Modeling to Examine Group Differences in Assessment Booklet Designs with Sparse Data
Willse, John T.; Goodman, Joshua T.; Allen, Nancy; Klaric, John
Applied Measurement in Education, v21 n3 p253-272 Jul 2008
The current research demonstrates the effectiveness of using structural equation modeling (SEM) for the investigation of subgroup differences with sparse data designs where not every student takes every item. Simulations were conducted that reflected missing data structures like those encountered in large survey assessment programs (e.g., National Assessment of Educational Progress). A maximum likelihood method of estimation was implemented that allowed all data to be used without performing any imputation. A multiple indicators multiple causes (MIMIC) model was used to examine group differences. There was no detriment to the estimation of the MIMIC model parameters under sparse data design conditions when compared to the design without missing data. The overall size of samples had more influence on the variability of estimates than did the data design. (Contains 3 figures, 1 footnote and 8 tables.)
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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: International Adult Literacy Survey