Baker, Frank B.Subkoviak, Michael J.2011-02-172011-02-171981Baker, Frank B & Subkoviak, Michael J. (1981). Analysis of test results via log-linear models. Applied Psychological Measurement, 5, 503-515. doi:10.1177/014662168100500408doi:10.1177/014662168100500408https://hdl.handle.net/11299/100423The 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.enArticle