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ERIC Number: EJ1083298
Record Type: Journal
Publication Date: 2015
Pages: 17
Abstractor: As Provided
ISSN: ISSN-0022-0655
Correcting Measurement Error in Latent Regression Covariates via the MC-SIMEX Method
Rutkowski, Leslie; Zhou, Yan
Journal of Educational Measurement, v52 n4 p359-375 Win 2015
Given the importance of large-scale assessments to educational policy conversations, it is critical that subpopulation achievement is estimated reliably and with sufficient precision. Despite this importance, biased subpopulation estimates have been found to occur when variables in the conditioning model side of a latent regression model contain measurement error. As such, this article proposes a method to correct for misclassification in the conditioning model by way of the misclassification simulation extrapolation (MC-SIMEX) method. Although the proposed method is computationally intensive, results from a simulation study show that the MC-SIMEX method improves latent regression coefficients and associated subpopulation achievement estimates. The method is demonstrated with PIRLS 2006 data. The importance of collecting high-priority, policy-relevant contextual data from at least two sources is emphasized and practical applications are discussed.
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Publication Type: Journal Articles; Reports - Research
Education Level: Grade 4; Intermediate Grades; Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Progress in International Reading Literacy Study
Grant or Contract Numbers: N/A