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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
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
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
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
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
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
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
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)
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

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
Allen, Nancy L.; Dunbar, Stephen B. – 1988
A recurring problem in educational research is how to account for non-random selection that has restricted the range of the variables of interest in correlational analyses. Several expressions due to H. Pearson (1903) and presented in matrix notation by D. N. Lawley (1943-44) are commonly used in selection settings to adjust for samples chosen on…
Descriptors: Computer Simulation, Correlation, Error of Measurement, Matrices
Hedges, Larry V.; Vevea, Jack L. – 2003
A computer simulation study was conducted to investigate the amount of uncertainty added to National Assessment of Educational Progress estimates by equating error under three different equating methods and while varying a number of factors that might affect accuracy of equating. Data from past NAEP administrations were used to guide the…
Descriptors: Computer Simulation, Equated Scores, Error of Measurement, Item Response Theory
DeMars, Christine E. – Educational and Psychological Measurement, 2005
Type I error rates for PARSCALE's fit statistic were examined. Data were generated to fit the partial credit or graded response model, with test lengths of 10 or 20 items. The ability distribution was simulated to be either normal or uniform. Type I error rates were inflated for the shorter test length and, for the graded-response model, also for…
Descriptors: Test Length, Item Response Theory, Psychometrics, Error of Measurement

Zimmerman, Donald W. – Educational and Psychological Measurement, 1985
A computer program simulated guessing on multiple-choice test items and calculated deviation IQ's from observed scores which contained a guessing component. Extensive variability in deviation IQ's due entirely to chance was found. (Author/LMO)
Descriptors: Computer Simulation, Error of Measurement, Guessing (Tests), Intelligence Quotient