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Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/100423

Title: Analysis of test results via log-linear models
Authors: Baker, Frank B.
Subkoviak, Michael J.
Issue Date: 1981
Citation: Baker, Frank B & Subkoviak, Michael J. (1981). Analysis of test results via log-linear models. Applied Psychological Measurement, 5, 503-515. doi:10.1177/014662168100500408
Abstract: The recently developed log-linear model procedures are applied to three types of data arising in a measurement context. First, because of the historical intersection of survey methods and test norming, the log-linear model approach should have direct utility in the analysis of norm-referenced test results. Several different schemes for analyzing the homogeneity of test score distributions are presented that provide a finer analysis of such data than was previously available. Second,the analysis of a contingency table resulting from the cross-classification of students on the basis of criterion-referenced test results and instructionally related variables is presented. Third, the intersection of log-linear models and item parameter estimation procedures under latent trait theory are shown. The illustrative examples in each of these areas suggest that log-linear models can be a versatile and useful data analysis technique in a measurement context.
URI: http://purl.umn.edu/100423
Appears in Collections:Volume 05, 1981

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