Skip to main content
Analysis of test results via log-linear models
Baker, Frank B.; Subkoviak, Michael J. (1981)

Analysis of test results via log-linear models

Issue Date


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.

Other Identifier(s)
other: doi:10.1177/014662168100500408

Previously Published 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

Suggested Citation
Baker, Frank B.; Subkoviak, Michael J.. (1981). Analysis of test results via log-linear models. Retrieved from the University of Minnesota Digital Conservancy,

Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.