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Corinne Huggins-Manley; Anthony W. Raborn; Peggy K. Jones; Ted Myers – Journal of Educational Measurement, 2024
The purpose of this study is to develop a nonparametric DIF method that (a) compares focal groups directly to the composite group that will be used to develop the reported test score scale, and (b) allows practitioners to explore for DIF related to focal groups stemming from multicategorical variables that constitute a small proportion of the…
Descriptors: Nonparametric Statistics, Test Bias, Scores, Statistical Significance
Dimitrov, Dimiter M. – Measurement and Evaluation in Counseling and Development, 2017
This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.
Descriptors: Test Bias, Item Response Theory, Factor Analysis, Evaluation Methods
Lin, Chih-Kai – Language Testing, 2017
Sparse-rated data are common in operational performance-based language tests, as an inevitable result of assigning examinee responses to a fraction of available raters. The current study investigates the precision of two generalizability-theory methods (i.e., the rating method and the subdividing method) specifically designed to accommodate the…
Descriptors: Data Analysis, Language Tests, Generalizability Theory, Accuracy
Landmesser, John Andrew – ProQuest LLC, 2014
Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…
Descriptors: Information Technology, Portfolio Assessment, Decision Making, Cognitive Processes
Itang'ata, Mukaria J. J. – ProQuest LLC, 2013
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Descriptors: Comparative Analysis, Probability, Statistical Bias, Monte Carlo Methods
Xu, Ting; Stone, Clement A. – Educational and Psychological Measurement, 2012
It has been argued that item response theory trait estimates should be used in analyses rather than number right (NR) or summated scale (SS) scores. Thissen and Orlando postulated that IRT scaling tends to produce trait estimates that are linearly related to the underlying trait being measured. Therefore, IRT trait estimates can be more useful…
Descriptors: Educational Research, Monte Carlo Methods, Measures (Individuals), Item Response Theory
Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)
Zhang, Bo; Ohland, Matthew W. – Applied Measurement in Education, 2009
One major challenge in using group projects to assess student learning is accounting for the differences of contribution among group members so that the mark assigned to each individual actually reflects their performance. This research addresses the validity of grading group projects by evaluating different methods that derive individualized…
Descriptors: Monte Carlo Methods, Validity, Student Evaluation, Evaluation Methods
de la Torre, Jimmy – Applied Psychological Measurement, 2008
Recent work has shown that multidimensionally scoring responses from different tests can provide better ability estimates. For educational assessment data, applications of this approach have been limited to binary scores. Of the different variants, the de la Torre and Patz model is considered more general because implementing the scoring procedure…
Descriptors: Markov Processes, Scoring, Data Analysis, Item Response Theory
Oshima, T. C.; Raju, Nambury S.; Nanda, Alice O. – Journal of Educational Measurement, 2006
A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score…
Descriptors: Evaluation Methods, Statistical Distributions, Statistical Significance, Test Bias
Kang, Sun-Mee; Waller, Niels G. – Applied Psychological Measurement, 2005
Two Monte Carlo studies were conducted to explore the Type I error rates in moderated multiple regression (MMR) of observed scores and estimated latent trait scores from a two-parameter logistic item response theory (IRT) model. The results of both studies showed that MMR Type I error rates were substantially higher than the nominal alpha levels…
Descriptors: Multiple Regression Analysis, Interaction, Monte Carlo Methods, Item Response Theory
Levy, Roy; Mislevy, Robert J. – US Department of Education, 2004
The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…
Descriptors: Probability, Markov Processes, Monte Carlo Methods, Bayesian Statistics
Ziomek, Robert L.; Szymczuk, Mike – 1983
In order to evaluate standard setting procedures, apart from the more commonly applied approach of simply comparing the derived standards or failure rates across various techniques, this study investigated the errors of classification associated with the contrasting groups procedures. Monte Carlo simulations were employed to produce…
Descriptors: Classification, Computer Simulation, Error of Measurement, Evaluation Methods