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Taylor, Aaron B.; West, Stephen G.; Aiken, Leona S. – Educational and Psychological Measurement, 2006
Variables that have been coarsely categorized into a small number of ordered categories are often modeled as outcome variables in psychological research. The authors employ a Monte Carlo study to investigate the effects of this coarse categorization of dependent variables on power to detect true effects using three classes of regression models:…
Descriptors: Regression (Statistics), Classification, Monte Carlo Methods, Sample Size
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Li, Yanmei; Bolt, Daniel M.; Fu, Jianbin – Applied Psychological Measurement, 2006
When tests are made up of testlets, standard item response theory (IRT) models are often not appropriate due to the local dependence present among items within a common testlet. A testlet-based IRT model has recently been developed to model examinees' responses under such conditions (Bradlow, Wainer, & Wang, 1999). The Bradlow, Wainer, and…
Descriptors: Models, Markov Processes, Item Response Theory, Tests
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Ferron, John; Jones, Peggy K. – Journal of Experimental Education, 2006
The authors present a method that ensures control over the Type I error rate for those who visually analyze the data from response-guided multiple-baseline designs. The method can be seen as a modification of visual analysis methods to incorporate a mechanism to control Type I errors or as a modification of randomization test methods to allow…
Descriptors: Multivariate Analysis, Data Analysis, Inferences, Monte Carlo Methods
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Jenson, William R.; Clark, Elaine; Kircher, John C.; Kristjansson, Sean D. – Psychology in the Schools, 2007
Evidence-based practice approaches to interventions has come of age and promises to provide a new standard of excellence for school psychologists. This article describes several definitions of evidence-based practice and the problems associated with traditional statistical analyses that rely on rejection of the null hypothesis for the…
Descriptors: School Psychologists, Statistical Analysis, Hypothesis Testing, Intervention
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Mariano, Louis T.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2007
When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…
Descriptors: Test Items, Item Response Theory, Rating Scales, Scoring
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Herzog, Walter; Boomsma, Anne; Reinecke, Sven – Structural Equation Modeling: A Multidisciplinary Journal, 2007
According to Kenny and McCoach (2003), chi-square tests of structural equation models produce inflated Type I error rates when the degrees of freedom increase. So far, the amount of this bias in large models has not been quantified. In a Monte Carlo study of confirmatory factor models with a range of 48 to 960 degrees of freedom it was found that…
Descriptors: Monte Carlo Methods, Structural Equation Models, Effect Size, Maximum Likelihood Statistics
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Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2007
The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…
Descriptors: Psychometrics, Computation, Reliability, Monte Carlo Methods
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Zientek, Linda Reichwein; Capraro, Mary Margaret; Capraro, Robert M. – Educational Researcher, 2008
The authors of this article examine the analytic and reporting features of research articles cited in "Studying Teacher Education: The Report of the AERA Panel on Research and Teacher Education" (Cochran-Smith & Zeichner, 2005b) that used quantitative reporting practices. Their purpose was to help to identify reporting practices that can be…
Descriptors: Preservice Teacher Education, Social Science Research, Intervals, Social Sciences
Donoghue, John R. – 1995
A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…
Descriptors: Algorithms, Cluster Analysis, Comparative Analysis, Correlation
Lix, Lisa M.; And Others – 1997
The Welch-James (WJ) and Improved General Approximation (IGA) tests for the within-subjects main and interaction effects in a split-plot repeated measurement design were investigated when least squares estimates and robust estimates based on trimmed means were used. Variables manipulated in the Monte Carlo study included the degree of multivariate…
Descriptors: Foreign Countries, Least Squares Statistics, Monte Carlo Methods, Research Design
Althouse, Linda Akel; Ware, William B.; Ferron, John M. – 1998
The assumption of normality underlies much of the standard statistical methodology. Knowing how to determine whether a sample of measurements is from a normally distributed population is crucial both in the development of statistical theory and in practice. W. Ware and J. Ferron have developed a new test statistic, modeled after the K-squared test…
Descriptors: Monte Carlo Methods, Power (Statistics), Sample Size, Simulation
Fouladi, Rachel T. – 1998
Covariance structure analytic techniques have become increasingly popular in recent years. During this period, users of statistical software packages have become more and more sophisticated, and more and more researchers are wanting to make sure that they are using the "best" statistic, whether it be for small sample considerations or…
Descriptors: Computer Software, Maximum Likelihood Statistics, Monte Carlo Methods, Multivariate Analysis
Spearing, Debra; Woehlke, Paula – 1989
To assess the effect on discriminant analysis in terms of correct classification into two groups, the following parameters were systematically altered using Monte Carlo techniques: sample sizes; proportions of one group to the other; number of independent variables; and covariance matrices. The pairing of the off diagonals (or covariances) with…
Descriptors: Classification, Correlation, Discriminant Analysis, Matrices
Klockars, Alan J.; Hancock, Gregory R. – 1990
Two strategies, derived from J. P. Schaffer (1986), were compared as tests of significance for a complete set of planned orthogonal contrasts. The procedures both maintain an experimentwise error rate at or below alpha, but differ in the manner in which they test the contrast with the largest observed difference. One approach proceeds directly to…
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Methodology
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Hummel, Thomas J.; Feltovich, Paul J. – Multivariate Behavioral Research, 1975
Monte Carlo methods were used to investigate the robustness of techniques used in judging the magnitude of a sample correlation coefficient when observations are correlated. Empirical distributions of r, t, and Fisher's z were generated. A technique for controlling error rates in certain situations is suggested. (Author/BJG)
Descriptors: Computer Science, Correlation, Error Patterns, Monte Carlo Methods
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