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Tanguma, Jesus – 2001
The purpose of this study was to investigate the effects of sample size on the power of five selected fit indices through a Monte Carlo simulation. Two models (a reduced and a complete model) and 6 sample sizes (20, 50, 100, 200, 500, and 1,000) were used to investigate the effect on the power of fit indices as the sample size was varied. The…
Descriptors: Goodness of Fit, Models, Monte Carlo Methods, Power (Statistics)
Barnette, J. Jackson; McLean, James E. – 2000
The probabilities of attaining varying magnitudes of standardized effect sizes by chance and when protected by a 0.05 level statistical test were studied. Monte Carlo procedures were used to generate standardized effect sizes in a one-way analysis of variance situation with 2 through 5, 6, 8, and 10 groups with selected sample sizes from 5 to 500.…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Probability
Romano, Jeanine; Kromrey, Jeffrey D. – 2002
The purpose of this study was to examine the potential impact of selected methodological factors on the validity of conclusions from reliability generalization (RG) studies. The study focused on four factors; (1) missing data in the primary studies; (2) transformation of sample reliability estimates; (3) use of sample weights for estimating mean…
Descriptors: Error of Measurement, Monte Carlo Methods, Reliability, Research Methodology
Vargha, Andras; Delaney, Harold D. – 2000
In this paper, six statistical tests of stochastic equality are compared with respect to Type I error and power through a Monte Carlo simulation. In the simulation, the skewness and kurtosis levels and the extent of variance heterogeneity of the two parent distributions were varied across a wide range. The sample sizes applied were either small or…
Descriptors: Comparative Analysis, Monte Carlo Methods, Robustness (Statistics), Sample Size
Lau, C. Allen; Wang, Tianyou – 1999
A study was conducted to extend the sequential probability ratio testing (SPRT) procedure with the polytomous model under some practical constraints in computerized classification testing (CCT), such as methods to control item exposure rate, and to study the effects of other variables, including item information algorithms, test difficulties, item…
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Peer reviewedGleason, Terry C.; Staelin, Richard – Psychometrika, 1973
In this paper a method is proposed whereby an investigator may improve the metric qualities of questionnaire and similar kinds of data. (Author)
Descriptors: Data Collection, Measurement, Monte Carlo Methods, Psychometrics
Peer reviewedFlynn, Michael J. – Mathematics Teacher, 1974
Descriptors: Calculus, Computers, Instruction, Mathematical Applications
Peer reviewedRock, Donald A.; And Others – Educational and Psychological Measurement, 1970
Descriptors: Monte Carlo Methods, Multiple Regression Analysis, Predictive Measurement, Predictor Variables
Peer reviewedLord, Frederic M. – Journal of Educational Statistics, 1982
The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared. (Author)
Descriptors: Equated Scores, Error of Measurement, Monte Carlo Methods, Test Construction
Peer reviewedRudner, Lawrence M.; And Others – Journal of Educational Measurement, 1980
Using Monte Carlo generated item response data, this research sought to determine the effectiveness, sufficiency and similarity of selected techniques for detecting item bias. The three-parameter latent-trait test model was used to generate the simulated data. (Author/JKS)
Descriptors: Item Analysis, Latent Trait Theory, Monte Carlo Methods, Test Bias
Peer reviewedKromrey, Jeffrey D.; Hines, Constance V. – Journal of Experimental Education, 1996
The accuracy of three analytical formulas for shrinkage estimation and four empirical techniques were investigated in a Monte Carlo study of the coefficient of cross-validity in multiple regression. Substantial statistical bias was evident for all techniques except the formula of M. W. Brown (1975) and multicross-validation. (SLD)
Descriptors: Estimation (Mathematics), Monte Carlo Methods, Regression (Statistics), Statistical Analysis
Peer reviewedHarwell, Michael – Journal of Educational and Behavioral Statistics, 2003
Used meta analytic methods to summarize results of Monte Carlo studies of test size and power of the F test in the single-factor, fixed-effects analysis of covariance model, updating and extending narrative reviews of this literature. (SLD)
Descriptors: Analysis of Covariance, Literature Reviews, Meta Analysis, Monte Carlo Methods
Peer reviewedHarwell, Michael – Journal of Experimental Education, 1997
The meta-analytic method proposed by S. W. Raudenbush (1988) for studying variance heterogeneity was studied. Results of a Monte Carlo study indicate that the Type I error rate of the test is sensitive to even modestly platykurtic score distributions and to the ratio of study sample size to the number of studies. (SLD)
Descriptors: Meta Analysis, Monte Carlo Methods, Research Reports, Sample Size
Peer reviewedMay, Kim; Hittner, James B. – Journal of Experimental Education, 1997
A Monte Carlo evaluation of four test statistics for comparing dependent zero-order correlations was conducted with four sample sizes and three population distributions. Results indicate that choice of optimal test statistic depends on sample size and distribution, and predictor intercorrelation and effect size or magnitude of the…
Descriptors: Correlation, Effect Size, Monte Carlo Methods, Predictor Variables
Peer reviewedCaruso, John C.; Cliff, Norman – Educational and Psychological Measurement, 1997
Several methods of constructing confidence intervals for Spearman's rho (rank correlation coefficient) (C. Spearman, 1904) were tested in a Monte Carlo study using 2,000 samples of 3 different sizes. Results support the continued use of Spearman's rho in behavioral research. (SLD)
Descriptors: Behavioral Science Research, Correlation, Monte Carlo Methods, Power (Statistics)


