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Showing 136 to 150 of 168 results Save | Export
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Fidalgo, Angel M.; Ferreres, Doris; Muniz, Jose – Journal of Experimental Education, 2004
The aim of this work was to determine, in terms of Type I and Type II error rates, the risks of applying various statistical procedures for evaluating differential item functioning. To this end, the authors carried out a simulation study in which the Mantel-Haenszel and SIBTEST procedures were applied in conjunction. The variables manipulated were…
Descriptors: Test Bias, Sample Size, Statistical Analysis, Predictor Variables
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Dudgeon, Paul – Structural Equation Modeling, 2004
This article considers the implications for other noncentrality parameter-based statistics from Steiger's (1998) multiple sample adjustment to the root mean square error of approximation (RMSEA) measure. When a structural equation model is fitted simultaneously in more than 1 sample, it is shown that the calculation of the noncentrality parameter…
Descriptors: Statistical Analysis, Monte Carlo Methods, Structural Equation Models, Error of Measurement
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Laufer, Batia – Applied Linguistics, 2005
This paper is a response to Paul Meara's (2005) critique of the Lexical Frequency Profile (LFP). Using simulated data, he challenges the claim that LFP is a sensitive and reliable tool for assessing vocabulary use in L2 speakers. In my response to his paper, I discuss the nature of lexical competence, in light of which LFP results should be…
Descriptors: Word Frequency, Lexicology, Profiles, Criticism
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Chen, Ru San; Dunlap, William P. – Journal of Educational Statistics, 1994
The present simulation study confirms that the corrected epsilon approximate test of B. Lecoutre yields a less biased estimation of population epsilon and reduces Type I error rates when compared to the epsilon approximate test of H. Huynh and L. S. Feldt. (SLD)
Descriptors: Computer Simulation, Estimation (Mathematics), Evaluation Methods, Monte Carlo Methods
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Savalei, Victoria; Bentler, Peter M. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
This article proposes a new approach to the statistical analysis of pairwisepresent covariance structure data. The estimator is based on maximizing the complete data likelihood function, and the associated test statistic and standard errors are corrected for misspecification using Satorra-Bentler corrections. A Monte Carlo study was conducted to…
Descriptors: Evaluation Methods, Maximum Likelihood Statistics, Statistical Analysis, Monte Carlo Methods
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Fan, Weihua; Hancock, Gregory R. – Educational and Psychological Measurement, 2006
In the common two-step structural equation modeling process, modifications are routinely made to the measurement portion of the model prior to assessing structural relations. The effect of such measurement model modifications on the structural parameter estimates, however, is not well known and is the subject of the current investigation. For a…
Descriptors: Error of Measurement, Evaluation Methods, Monte Carlo Methods, Sample Size
Moy, Mabel L. Y.; Barcikowski, Robert S. – 1973
Using a computer-based Monte Carlo approach to generate item responses, the results of this study indicate that, when item discrimination indices are considered, item-examinee sampling procedures having the same number of observations have different standard errors in estimating both test mean and test variance. With certain types of tests, a…
Descriptors: Error of Measurement, Evaluation Methods, Item Sampling, Monte Carlo Methods
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Rich, Joseph R.; Boudreau, John W. – Personnel Psychology, 1987
Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…
Descriptors: Decision Making, Evaluation Methods, Human Resources, Labor Utilization
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Ramsey, Philip H. – Journal of Educational Statistics, 1982
Monte Carlo results were used to evaluate procedures for discriminating between groups. A multiple testing version of Hotelling's T-squared and the Bonferroni procedure were most powerful for detecting at least one true difference, depending on conditions examined. A multiple Bonferroni procedure was superior in power for detecting all true…
Descriptors: Data Analysis, Educational Research, Evaluation Methods, Monte Carlo Methods
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Roznowski, Mary; And Others – Applied Psychological Measurement, 1991
Three heuristic methods of assessing the dimensionality of binary item pools were evaluated in a Monte Carlo investigation. The indices were based on (1) the local independence of unidimensional tests; (2) patterns of second-factor loadings derived from simplex theory; and (3) the shape of the curve of successive eigenvalues. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Evaluation Methods
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Ogasawara, Haruhiko – Psychometrika, 2004
Formulas for the asymptotic biases of the parameter estimates in structural equation models are provided in the case of the Wishart maximum likelihood estimation for normally and nonnormally distributed variables. When multivariate normality is satisfied, considerable simplification is obtained for the models of unstandardized variables. Formulas…
Descriptors: Evaluation Methods, Bias, Factor Analysis, Structural Equation Models
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Oshima, T. C.; Raju, Nambury S.; Nanda, Alice O. – Journal of Educational Measurement, 2006
A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score…
Descriptors: Evaluation Methods, Statistical Distributions, Statistical Significance, Test Bias
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Hartz, Sarah; Roussos, Louis – ETS Research Report Series, 2008
This paper presents the development of the fusion model skills diagnosis system (fusion model system), which can help integrate standardized testing into the learning process with both skills-level examinee parameters for modeling examinee skill mastery and skills-level item parameters, giving information about the diagnostic power of the test.…
Descriptors: Skill Development, Educational Diagnosis, Theory Practice Relationship, Standardized Tests
Sadek, Ramses F.; Huberty, Carl J. – 1994
This study presents an overview of Monte Carlo studies in discriminant analysis. Some common questions about the use of Monte Carlo techniques are answered through a brief literature review of articles on discriminant analysis in which Monte Carlo methods are used. The articles cover many research points, such as comparing error rate estimates,…
Descriptors: Discriminant Analysis, Estimation (Mathematics), Evaluation Methods, Foreign Countries
Elashoff, Janet Dixon; Elashoff, Robert M. – 1971
The problem of comparing proportions when some data are missing is investigated, and determination is made of what statistical techniques are appropriate under each of several probability models describing the observations likely to be missing. Monte Carlo methods were used to investigate the properties of standard estimators under each of the…
Descriptors: Comparative Analysis, Data Analysis, Educational Research, Evaluation Methods
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