Journal of Educational Measurement 

About: Journal of Educational Measurement is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Item response theory & Test (assessment). It has an ISSN identifier of 0022-0655. Over the lifetime, 1669 publications have been published receiving 70688 citations. The journal is also known as: J E M.

Modern Multidimensional Scaling: Theory and Applications

Abstract: Fundamentals of MDS.- The Four Purposes of Multidimensional Scaling.- Constructing MDS Representations.- MDS Models and Measures of Fit.- Three Applications of MDS.- MDS and Facet Theory.- How to Obtain Proximities.- MDS Models and Solving MDS Problems.- Matrix Algebra for MDS.- A Majorization Algorithm for Solving MDS.- Metric and Nonmetric MDS.- Confirmatory MDS.- MDS Fit Measures, Their Relations, and Some Algorithms.- Classical Scaling.- Special Solutions, Degeneracies, and Local Minima.- Unfolding.- Unfolding.- Avoiding Trivial Solutions in Unfolding.- Special Unfolding Models.- MDS Geometry as a Substantive Model.- MDS as a Psychological Model.- Scalar Products and Euclidean Distances.- Euclidean Embeddings.- MDS and Related Methods.- Procrustes Procedures.- Three-Way Procrustean Models.- Three-Way MDS Models.- Modeling Asymmetric Data.- Methods Related to MDS.

Validating the Interpretations and Uses of Test Scores

Abstract: To validate an interpretation or use of test scores is to evaluate the plausibility of the claims based on the scores. An argument-based approach to validation suggests that the claims based on the test scores be outlined as an argument that specifies the inferences and supporting assumptions needed to get from test responses to score-based interpretations and uses. Validation then can be thought of as an evaluation of the coherence and completeness of this interpretation/use argument and of the plausibility of its inferences and assumptions. In outlining the argument-based approach to validation, this paper makes eight general points. First, it is the proposed score interpretations and uses that are validated and not the test or the test scores. Second, the validity of a proposed interpretation or use depends on how well the evidence supports the claims being made. Third, more-ambitious claims require more support than less-ambitious claims. Fourth, more-ambitious claims (e.g., construct interpretations) tend to be more useful than less-ambitious claims, but they are also harder to validate. Fifth, interpretations and uses can change over time in response to new needs and new understandings leading to changes in the evidence needed for validation. Sixth, the evaluation of score uses requires an evaluation of the consequences of the proposed uses; negative consequences can render a score use unacceptable. Seventh, the rejection of a score use does not necessarily invalidate a prior, underlying score interpretation. Eighth, the validation of the score interpretation on which a score use is based does not validate the score use.

Detecting Differential Item Functioning Using Logistic Regression Procedures

Abstract: A logistic regression model for characterizing differential item functioning (DIF) between two groups is presented. A distinction is drawn between uniform and nonuniform DIF in terms of the parameters of the model. A statistic for testing the hypothesis of no DIF is developed. Through simulation studies, it is shown that the logistic regression procedure is more powerful than the Mantel-Haenszel procedure for detecting nonuniform DIF and as powerful in detecting uniform DIF.

Hayes, Andrew F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: The Guilford Press

Abstract: Regression-based analyses remain some of the most widely employed statistical approaches throughout research and scholarly work. It is remarkable that with the same simple OLS multiple regression model, such a rich variety of research questions may be addressed, ranging from simple questions of prediction and explanation to the more complex questions such as modeling mediated or moderated relationships or even modeling of moderated mediation analyses. Hayes’s Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach presents a journey through regression-based approaches beginning with the most simple regression approaches (correlation and simple linear regression), continuing through traditional uses of regression for mediation and moderation analysis, and culminating in a discussion of conditional process analysis: a method for combining mediation and moderation into one singular analysis. The book is very readable and conversational, providing many interesting and useful examples, which will be of interest to the intermediate to advanced regression user.

Rule space: an approach for dealing with misconceptions based on item response theory

Abstract: Several authors from various disciplines such as cognitive psychology, artificial intelligence, and psychometrics have developed rule assessment methods for diagnosing students' misconceptions. Siegler's (1976, 1978) binary decision tree method was illustrated in the context of the problem of balance scales and Anderson's (1974, 1981) functional method was developed for diagnosing errors occurring during the operation of integrating functional rules. A group of artificial intelligence researchers (Brown & Burton, 1978; Brown & VanLehn, 1980; VanLehn, 1981) developed a computer program "DEBUGGY" that can diagnose a number of erroneous rules resulting from misconceptions ("bugs") in whole number subtraction problems. These investigations were motivated by an interest in the basic foundations of knowledge structure and development in human cognition. Tatsuoka and her associates (Tatsuoka, Baillie, & Yamamoto, 1982; Tatsuoka, Birenbaum, Tatsuoka, & Baillie, 1980) also developed a computer program that can diagnose a number of erroneous rules in signed-number addition and subtraction problems, but they were motivated primarily by the exploration of psychometric properties of bugs such as changes in error types or the stability of misconceptions committed by a student throughout a test (Birenbaum & Tatsuoka, 1980; Tatsuoka, 1981; Tatsuoka & Tatsuoka, 1983). Analysis of misconceptions can provide useful information in evaluating instruction or instructional materials as well as specific prescriptions for planning remediation for a student. For example, the source of many of the misconceptions committed by students is often the ambiguity of explanations or the lack of precise, accurate instructions in teaching material. It is useful to have such computer programs in educational practice. However, constructing a DEBUGGY-type system for domains more general than arithmetic is extremely difficult and time consuming. On the other hand, personal indices that are designed to summarize response patterns can be used for detecting anomalous patterns (Drasgow, 1982; Harnisch & Linn, 1981; Levine & Rubin, 1979; Sato, 1975; Tatsuoka & Tatsuoka, 1982; Wright & Stone, 1979) which may result from applications of some erroneous rules, but they have only limited power. For instance, these indices cannot diagnose sources of misconceptions or provide prescriptive information for remediating them. Nevertheless, the use of personal indices is economical and applicable to general areas because such indices can first be used to spot candidates among students who may possibly possess misconceptions and may hence need personal attention from teachers. This procedure seems to be widely used in Japan (Sato, 1982). This study develops a model to fill the gap between the rule-assessing methods and the personal-index approach. The number of different erroneous rules already discovered in