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Huang, Francis L. – Educational and Psychological Measurement, 2018
Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…
Descriptors: Multivariate Analysis, Sampling, Statistical Inference, Data Analysis
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Padilla, Miguel A.; Divers, Jasmin – Educational and Psychological Measurement, 2016
Coefficient omega and alpha are both measures of the composite reliability for a set of items. Unlike coefficient alpha, coefficient omega remains unbiased with congeneric items with uncorrelated errors. Despite this ability, coefficient omega is not as widely used and cited in the literature as coefficient alpha. Reasons for coefficient omega's…
Descriptors: Reliability, Computation, Statistical Analysis, Comparative Analysis
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Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi – Educational and Psychological Measurement, 2014
When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…
Descriptors: Sampling, Statistical Inference, Maximum Likelihood Statistics, Computation
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Chen, Pei-Hua; Chang, Hua-Hua; Wu, Haiyan – Educational and Psychological Measurement, 2012
Two sampling-and-classification-based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test…
Descriptors: Test Items, Selection, Test Construction, Item Response Theory
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Finch, W. Holmes; French, Brian F. – Educational and Psychological Measurement, 2012
Effect size use has been increasing in the past decade in many research areas. Confidence intervals associated with effect sizes are encouraged to be reported. Prior work has investigated the performance of confidence interval estimation with Cohen's d. This study extends this line of work to the analysis of variance case with more than two…
Descriptors: Computation, Statistical Analysis, Effect Size, Comparative Analysis
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Peng, Chao-Ying Joanne; Zhu, Jin – Educational and Psychological Measurement, 2008
For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…
Descriptors: Regression (Statistics), Comparative Analysis, Evaluation Methods, Equations (Mathematics)
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Wilcox, Rand R. – Educational and Psychological Measurement, 2006
For two random variables, X and Y, let D = X - Y, and let theta[subscript x], theta[subscript y], and theta[subscript d] be the corresponding medians. It is known that the Wilcoxon-Mann-Whitney test and its modern extensions do not test H[subscript o] : theta[subscript x] = theta[subscript y], but rather, they test H[subscript o] : theta[subscript…
Descriptors: Scores, Inferences, Comparative Analysis, Statistical Analysis
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Feir-Walsh, Betty J.; Toothaker, Larry E. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Hypothesis Testing, Nonparametric Statistics
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Subkoviak, Michael J. – Educational and Psychological Measurement, 1974
Descriptors: Comparative Analysis, Sampling, True Scores
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Kleinke, David J. – Educational and Psychological Measurement, 1972
Descriptors: Analysis of Variance, Comparative Analysis, Norms, Prediction
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Carroll, Robert M.; Nordholm, Lena A. – Educational and Psychological Measurement, 1975
Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)
Descriptors: Analysis of Variance, Bias, Comparative Analysis, Correlation
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LeBlanc, William G.; Williams, Richard H. – Educational and Psychological Measurement, 1997
The Statistical Analysis System was used to program a statistical procedure developed by K. J. Levy (1975). The focus was on Dunnett-like pairwise multiple comparisons among sample variances. An example using data from G. Glass and K. Hopkins (1996) is used to illustrate a computer run with this program. (Author/SLD)
Descriptors: Comparative Analysis, Computation, Sampling
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LeBlanc, William G.; Williams, Richard H. – Educational and Psychological Measurement, 1997
A large sample technique attributed to L. Marascuilo, based on the multiple comparison technique of H. Scheffe, was programmed with the Statistical Analysis System (SAS), focusing on comparisons among independent binomial samples. Use of the SAS program is discussed. (SLD)
Descriptors: Comparative Analysis, Computer Software, Sample Size, Sampling
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Pedulla, Joseph J.; Airasian, Peter W. – Educational and Psychological Measurement, 1980
Estimates of population values obtained using three sampling techniques (simple random sampling, stratified random sampling, and cluster sampling) and three size samples for each technique (10%, 25% and 50%) were compared with known "population" values. 25% simple random sample provided quite good estimates of the "population"…
Descriptors: Comparative Analysis, Elementary Secondary Education, Feasibility Studies, Foreign Countries
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Keselman, H. J.; And Others – Educational and Psychological Measurement, 1976
Compares the harmonic mean and Kramer unequal group forms of the Tukey test for various: (a) degrees of disparate group sizes, (b) numbers of groups, and (c) nominal significant levels. (RC)
Descriptors: Comparative Analysis, Probability, Sampling, Statistical Significance
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