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Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – Measurement: Interdisciplinary Research and Perspectives, 2020
Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychological measurement. When normality is assumed, asymmetry in the actual latent ability distribution has been shown to result in extraction of spurious…
Descriptors: Item Response Theory, Ability, Statistical Distributions, Sample Size
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Diwakar, Rekha – Practical Assessment, Research & Evaluation, 2017
Many existing methods of statistical inference and analysis rely heavily on the assumption that the data are normally distributed. However, the normality assumption is not fulfilled when dealing with data which does not contain negative values or are otherwise skewed--a common occurrence in diverse disciplines such as finance, economics, political…
Descriptors: Statistical Inference, Statistical Distributions, Research, Foreign Countries
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Wyse, Adam E.; Babcock, Ben – Educational Measurement: Issues and Practice, 2017
This article provides an overview of the Hofstee standard-setting method and illustrates several situations where the Hofstee method will produce undefined cut scores. The situations where the cut scores will be undefined involve cases where the line segment derived from the Hofstee ratings does not intersect the score distribution curve based on…
Descriptors: Cutting Scores, Evaluation Methods, Standard Setting (Scoring), Comparative Analysis
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2018
Wollack, Cohen, and Eckerly suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This article suggests two modifications of the EDI for…
Descriptors: Deception, Identification, Testing Problems, Cheating
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Nordstokke, David W.; Colp, S. Mitchell – Practical Assessment, Research & Evaluation, 2018
Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…
Descriptors: Nonparametric Statistics, Statistical Analysis, Monte Carlo Methods, Sample Size
Tong, Xin; Zhang, Zhiyong – Grantee Submission, 2020
Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…
Descriptors: Robustness (Statistics), Bayesian Statistics, Models, Error of Measurement
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Simpson, Adrian – Educational Researcher, 2019
A recent paper uses Bayes factors to argue a large minority of rigorous, large-scale education RCTs are "uninformative." The definition of "uninformative" depends on the authors' hypothesis choices for calculating Bayes factors. These arguably overadjust for effect size inflation and involve a fixed prior distribution,…
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Educational Research, Program Evaluation
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Trafimow, David – Educational and Psychological Measurement, 2018
Because error variance alternatively can be considered to be the sum of systematic variance associated with unknown variables and randomness, a tripartite assumption is proposed that total variance in the dependent variable can be partitioned into three variance components. These are variance in the dependent variable that is explained by the…
Descriptors: Statistical Analysis, Correlation, Experiments, Effect Size
Setyani, Geovani Debby; Kristanto, Yosep Dwi – Online Submission, 2020
Drawing inference from data is an important skill for students to understand their everyday life, so that the sampling distribution as a central topic in statistical inference is necessary to be learned by the students. However, little is known about how to teach the topic for high school students, especially in Indonesian context. Therefore, the…
Descriptors: High School Students, Grade 11, Private Schools, Foreign Countries
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Castillo, Felipe Aravena; Hallinger, Philip – Educational Management Administration & Leadership, 2018
The purpose of this systematic review was to further our understanding of educational leadership and management (EDLM) knowledge production in Latin America. We conducted a "topographical review" of 48 articles from Latin America published in eight "core" EDLM journals published between 1991 and 2017. Data analysis focused on…
Descriptors: Literature Reviews, Educational Administration, Leadership, Governance
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Ames, Allison J. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior…
Descriptors: Bayesian Statistics, Item Response Theory, Statistical Inference, Prediction
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2017
An increasing concern of producers of educational assessments is fraudulent behavior during the assessment (van der Linden, 2009). Benefiting from item preknowledge (e.g., Eckerly, 2017; McLeod, Lewis, & Thissen, 2003) is one type of fraudulent behavior. This article suggests two new test statistics for detecting individuals who may have…
Descriptors: Test Items, Cheating, Testing Problems, Identification
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Page, Robert B.; Espinosa, James; Mares, Chris A.; Del Pilar, Joselyn; Shelton, G. Robert – Journal of College Science Teaching, 2018
Education is frequently cited as the path to an informed citizenry with an optimistic economic outlook. Consequently, it is not surprising that there is an initiative to extend postsecondary educational opportunities to underserved and at-risk demographics. A challenge facing educators that serve at-risk populations is the tension between…
Descriptors: At Risk Students, STEM Education, Academic Achievement, Statistical Distributions
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Budgett, Stephanie; Pfannkuch, Maxine – ZDM: The International Journal on Mathematics Education, 2018
Randomness and distribution are important concepts underpinning the ability to think and reason probabilistically. Traditional approaches to teaching the Poisson distribution focus on mathematical definitions and formulae which obscure the randomness intrinsic in this process. Advances in technology have made it possible for students learning…
Descriptors: Mathematical Logic, Mathematical Concepts, Mathematics Instruction, Probability
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McCann, Lee I.; Ebert, Alexandria R.; Timmins, Rebecca R.; Thompson, Ashley E. – Teaching of Psychology, 2017
The present study examined changes in the genders of authors, first authors, reviewers, and editorial staff over 42 years (1974-2015) in "Teaching of Psychology." Over the first 6 years of the journal's publication, 17.67% of authors and 16.5% of first authors were women, increasing to 57.83% and 44% in the most recent 6 years. From the…
Descriptors: Authors, Editing, Gender Differences, Psychology
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