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Bockenholt, Ulf – Psychological Methods, 2012
In this article, I show how item response models can be used to capture multiple response processes in psychological applications. Intuitive and analytical responses, agree-disagree answers, response refusals, socially desirable responding, differential item functioning, and choices among multiple options are considered. In each of these cases, I…
Descriptors: Item Response Theory, Models, Responses, Selection
Goldhaber, Dan; Chaplin, Duncan – Mathematica Policy Research, Inc., 2012
In a provocative and influential paper, Jesse Rothstein (2010) finds that standard value-added models (VAMs) suggest implausible future teacher effects on past student achievement, a finding that obviously cannot be viewed as causal. This is the basis of a falsification test (the Rothstein falsification test) that appears to indicate bias in VAM…
Descriptors: Value Added Models, Academic Achievement, Teacher Effectiveness, Correlation
Schuster, Christof; Yuan, Ke-Hai – Journal of Educational and Behavioral Statistics, 2011
Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…
Descriptors: Computation, Item Response Theory, Probability, Maximum Likelihood Statistics
Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul – International Journal of Testing, 2011
We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…
Descriptors: Language Skills, Identification, Foreign Countries, Evaluation Methods
Camilli, Gregory; Prowker, Adam; Dossey, John A.; Lindquist, Mary M.; Chiu, Ting-Wei; Vargas, Sadako; de la Torre, Jimmy – Journal of Educational Measurement, 2008
A new method for analyzing differential item functioning is proposed to investigate the relative strengths and weaknesses of multiple groups of examinees. Accordingly, the notion of a conditional measure of difference between two groups (Reference and Focal) is generalized to a conditional variance. The objective of this article is to present and…
Descriptors: Test Bias, National Competency Tests, Grade 4, Difficulty Level
Boruch, Robert – New Directions for Evaluation, 2007
Thomas Jefferson recognized the value of reason and scientific experimentation in the eighteenth century. This chapter extends the idea in contemporary ways to standards that may be used to judge the ethical propriety of randomized trials and the dependability of evidence on effects of social interventions.
Descriptors: Ethics, Standards, Evaluation Methods, Research Methodology
Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…
Descriptors: Computation, Goodness of Fit, Test Bias, Statistical Analysis
Van den Noortgate, Wim; De Boeck, Paul – Journal of Educational and Behavioral Statistics, 2005
Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model…
Descriptors: Test Bias, Item Response Theory, Educational Assessment, Mathematical Models

Croy, Calvin D.; Novins, Douglas K. – Journal of the American Academy of Child and Adolescent Psychiatry, 2005
Objective: First, to provide information about best practices in handling missing data so that readers can judge the quality of research studies. Second, to provide more detailed information about missing data analysis techniques and software on the Journal's Web site at www.jaacap.com. Method: We focus our review of techniques on those that are…
Descriptors: Information Needs, Data Collection, Statistical Analysis, Maximum Likelihood Statistics