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Metsämuuronen, Jari – International Journal of Educational Methodology, 2020
Kelley's Discrimination Index (DI) is a simple and robust, classical non-parametric short-cut to estimate the item discrimination power (IDP) in the practical educational settings. Unlike item-total correlation, DI can reach the ultimate values of +1 and -1, and it is stable against the outliers. Because of the computational easiness, DI is…
Descriptors: Test Items, Computation, Item Analysis, Nonparametric Statistics
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Yukhymenko-Lescroart, Mariya A.; Goldman, Susan R.; Lawless, Kimberly A.; Pellegrino, James W.; Shanahan, Cynthia R. – Educational Psychology, 2022
To extend the existing research examining multiple text comprehension and its assessment, we developed a verification task approach to assessing of information that was "explicitly" and "implicitly" presented "within" and across nine texts. A nonparametric form of signal detection theory was used to analyse the…
Descriptors: Task Analysis, Reading Comprehension, Middle School Students, Nonparametric Statistics
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Lee, HyeSun; Smith, Weldon; Martinez, Angel; Ferris, Heather; Bova, Joe – Applied Measurement in Education, 2021
The aim of the current research was to provide recommendations to facilitate the development and use of anchoring vignettes (AVs) for cross-cultural comparisons in education. Study 1 identified six factors leading to order violations and ties in AV responses based on cognitive interviews with 15-year-old students. The factors were categorized into…
Descriptors: Vignettes, Test Items, Equated Scores, Nonparametric Statistics
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Wind, Stefanie A. – Language Testing, 2019
Differences in rater judgments that are systematically related to construct-irrelevant characteristics threaten the fairness of rater-mediated writing assessments. Accordingly, it is essential that researchers and practitioners examine the degree to which the psychometric quality of rater judgments is comparable across test-taker subgroups.…
Descriptors: Nonparametric Statistics, Interrater Reliability, Differences, Writing Tests
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Wind, Stefanie A. – Measurement: Interdisciplinary Research and Perspectives, 2020
A major challenge in the widespread application of Mokken scale analysis (MSA) to educational performance assessments is the requirement of complete data, where every rater rates every student. In this study, simulated and real data are used to demonstrate a method by which researchers and practitioners can apply MSA to incomplete rating designs.…
Descriptors: Item Response Theory, Scaling, Nonparametric Statistics, Performance Based Assessment
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Walter M. Stroup; Anthony Petrosino; Corey Brady; Karen Duseau – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
Tests of statistical significance often play a decisive role in establishing the empirical warrant of evidence-based research in education. The results from pattern-based assessment items, as introduced in this paper, are categorical and multimodal and do not immediately support the use of measures of central tendency as typically related to…
Descriptors: Statistical Significance, Comparative Analysis, Research Methodology, Evaluation Methods
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Ghaemi, Hamed – Language Testing in Asia, 2022
Listening comprehension in English, as one of the most fundamental skills, has an essential role in the process of learning English. Mokken scale analysis (MSA) is a probabilistic-nonparametric approach to item response theory (IRT) which determines the one-dimensionality and scalability of test. Mokken scaling techniques are a useful tool for…
Descriptors: Second Language Learning, English (Second Language), Nonparametric Statistics, Item Response Theory
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Cynthia A. Gallardo – School Leadership Review, 2024
Dual Enrollment (DE) or Dual Credit (DC) programs have become increasingly prevalent at both the high school and college settings. These programs enable students to earn both high school and college credit and get a head start on their college education. Additionally, students in these programs must take university core curriculum courses to…
Descriptors: Introductory Courses, Biology, Dual Enrollment, High Schools
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Ayanwale, Musa Adekunle; Ndlovu, Mdutshekelwa – Education Sciences, 2021
This study investigated the scalability of a cognitive multiple-choice test through the Mokken package in the R programming language for statistical computing. A 2019 mathematics West African Examinations Council (WAEC) instrument was used to gather data from randomly drawn K-12 participants (N = 2866; Male = 1232; Female = 1634; Mean age = 16.5…
Descriptors: Cognitive Tests, Multiple Choice Tests, Scaling, Test Items
Enakshi Saha – ProQuest LLC, 2021
We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…
Descriptors: Bayesian Statistics, Probability, Nonparametric Statistics, Data Analysis
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Dimitrov, Dimiter M.; Atanasov, Dimitar V.; Luo, Yong – Measurement: Interdisciplinary Research and Perspectives, 2020
This study examines and compares four person-fit statistics (PFSs) in the framework of the "D"- scoring method (DSM): (a) van der Flier's "U3" statistic; (b) "Ud" statistic, as a modification of "U3" under the DSM; (c) "Zd" statistic, as a modification of the "Z3 (l[subscript z])"…
Descriptors: Goodness of Fit, Item Analysis, Item Response Theory, Scoring
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Keller, Bryan – Journal of Educational and Behavioral Statistics, 2020
Widespread availability of rich educational databases facilitates the use of conditioning strategies to estimate causal effects with nonexperimental data. With dozens, hundreds, or more potential predictors, variable selection can be useful for practical reasons related to communicating results and for statistical reasons related to improving the…
Descriptors: Nonparametric Statistics, Computation, Testing, Causal Models
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Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
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Liu, Yang; Wang, Xiaojing – Journal of Educational and Behavioral Statistics, 2020
Parametric methods, such as autoregressive models or latent growth modeling, are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time gap is irregular and the recorded time points are individually varying. Often in practice, the growth trend of latent traits is subject to certain…
Descriptors: Bayesian Statistics, Nonparametric Statistics, Regression (Statistics), Item Response Theory
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Powell, Marvin G.; Hull, Darrell M.; Beaujean, A. Alexander – Journal of Experimental Education, 2020
Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the…
Descriptors: Probability, Scores, Observation, Educational Research
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