Browsing by Author "Subkoviak, Michael J."
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Item Analysis of test results via log-linear models(1981) Baker, Frank B.; Subkoviak, Michael J.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.Item Correcting "Planning an experiment in the company of measurement error"(1978) Levin, Joel R.; Subkoviak, Michael J.Comments on our earlier article are acknowledged and appreciated. In addition, potentially misleading notions arising from these comments are addressed and clarified.Item Planning an experiment in the company of measurement error(1977) Levin, Joel R.; Subkoviak, Michael J."Textbook" calculations of statistical power and/or sample size follow from formulas that assume that the variables under consideration are measured without error. However, in the "real world" of behavioral research, errors of measurement cannot be neglected. A recent sample-size determination approach is easily adapted to incorporate unreliability information for both completely randomized and randomized block analysis-of-variance designs. A worked example presents an instance wherein a blocking strategy is clearly advantageous assuming infallible measuring instruments, but not when the same instruments are granted fallibility.