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Arel-Bundock, Vincent – Sociological Methods & Research, 2022
Qualitative comparative analysis (QCA) is an influential methodological approach motivated by set theory and boolean logic. QCA proponents have developed algorithms to analyze quantitative data, in a bid to uncover necessary and sufficient conditions where causal relationships are complex, conditional, or asymmetric. This article uses computer…
Descriptors: Comparative Analysis, Qualitative Research, Attribution Theory, Computer Simulation
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Shear, Benjamin R.; Nordstokke, David W.; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2018
This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher…
Descriptors: Nonparametric Statistics, Computer Simulation, Monte Carlo Methods, Sampling
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Weng, Cathy; Puspitasari, Dani; Tran, Khanh Nguyen Phuong; Feng, Pei Jie; Awuor, Nicholas O.; Matere, Isaac Manyonge – Interactive Learning Environments, 2023
The purpose of this study was to investigate the effect of augmented reality (AR) using a 3D app in a smartphone on students' learning outcomes and satisfaction in teaching angle measurement error to vocational high school students with different spatial ability. A quasi-experimental pretest/posttest was employed. There were 197 students from…
Descriptors: Teaching Methods, Error of Measurement, Multimedia Instruction, Learning Processes
Bukhari, Nurliyana – ProQuest LLC, 2017
In general, newer educational assessments are deemed more demanding challenges than students are currently prepared to face. Two types of factors may contribute to the test scores: (1) factors or dimensions that are of primary interest to the construct or test domain; and, (2) factors or dimensions that are irrelevant to the construct, causing…
Descriptors: Item Response Theory, Models, Psychometrics, Computer Simulation
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Culbertson, Michael J. – Regional Educational Laboratory Central, 2016
States in the Regional Educational Laboratory (REL) Central region serve a largely rural population with many states enrolling fewer than 350,000 students. A common challenge identified among REL Central educators is identifying appropriate methods for analyzing data with small samples of students. In particular, members of the REL Central…
Descriptors: Student Development, Sample Size, Academic Achievement, Scores
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Temel, Gülhan Orekici; Erdogan, Semra; Selvi, Hüseyin; Kaya, Irem Ersöz – Educational Sciences: Theory and Practice, 2016
Studies based on longitudinal data focus on the change and development of the situation being investigated and allow for examining cases regarding education, individual development, cultural change, and socioeconomic improvement in time. However, as these studies require taking repeated measures in different time periods, they may include various…
Descriptors: Investigations, Sample Size, Longitudinal Studies, Interrater Reliability
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2014
Publication selection bias is a serious challenge to the integrity of all empirical sciences. We derive meta-regression approximations to reduce this bias. Our approach employs Taylor polynomial approximations to the conditional mean of a truncated distribution. A quadratic approximation without a linear term, precision-effect estimate with…
Descriptors: Regression (Statistics), Bias, Algebra, Mathematical Formulas
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Shear, Benjamin R.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2013
Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…
Descriptors: Error of Measurement, Multiple Regression Analysis, Data Analysis, Computer Simulation
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Skrondal, Anders; Kuha, Jouni – Psychometrika, 2012
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Descriptors: Computation, Maximum Likelihood Statistics, Error of Measurement, Regression (Statistics)
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Kim, Seonghoon; Feldt, Leonard S. – Journal of Educational Measurement, 2008
This article extends the Bonett (2003a) approach to testing the equality of alpha coefficients from two independent samples to the case of m [greater than or equal] 2 independent samples. The extended Fisher-Bonett test and its competitor, the Hakstian-Whalen (1976) test, are illustrated with numerical examples of both hypothesis testing and power…
Descriptors: Tests, Comparative Analysis, Hypothesis Testing, Error of Measurement
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Fidalgo, Angel M.; Hashimoto, Kanako; Bartram, Dave; Muniz, Jose – Journal of Experimental Education, 2007
In this study, the authors assess several strategies created on the basis of the Mantel-Haenszel (MH) procedure for conducting differential item functioning (DIF) analysis with small samples. One of the analytical strategies is a loss function (LF) that uses empirical Bayes Mantel-Haenszel estimators, whereas the other strategies use the classical…
Descriptors: Bayesian Statistics, Test Bias, Statistical Analysis, Sample Size
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Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2002
Used Johnson's transformation (N. Johnson, 1978) with approximate test statistics to test the homogeneity of simple linear regression slopes in the presence of nonnormality and Type I, Type II or complete heteroscedasticity. Computer simulations show that the proposed techniques can control Type I error under various circumstances. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Regression (Statistics)
Robey, Randall R.; Barcikowski, Robert S. – 1989
In analyzing exploratory repeated measures data with more than two measures, two competing tests must be administered simultaneously if one is to make an efficient and effective decision regarding the tenability of the null hypothesis of no differences among measurement means. Obviously, such a procedure is not without a cost vis-a-vis Type I…
Descriptors: Algorithms, Computer Simulation, Error of Measurement, Hypothesis Testing
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Kluge, Annette – Applied Psychological Measurement, 2008
The use of microworlds (MWs), or complex dynamic systems, in educational testing and personnel selection is hampered by systematic measurement errors because these new and innovative item formats are not adequately controlled for their difficulty. This empirical study introduces a way to operationalize an MW's difficulty and demonstrates the…
Descriptors: Personnel Selection, Self Efficacy, Educational Testing, Computer Uses in Education
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Zeng, Lingjia; And Others – Applied Psychological Measurement, 1994
A general delta method is described for computing the standard error (SE) of a chain of linear equations. The general delta method derives the SEs directly from the moments of the score distributions obtained in the equating chain. Computer simulations demonstrate the method. (SLD)
Descriptors: Computer Simulation, Equated Scores, Error of Measurement, Statistical Distributions
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