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Aaron, Bruce C.; Kromrey, Jeffrey D. – 1998
In a Monte Carlo analysis of single-subject data, Type I and Type II error rates were compared for various statistical tests of the significance of treatment effects. Data for 5,000 subjects in each of 6 treatment effect size groups were computer simulated, and 2 types of treatment effects were simulated in the dependent variable during…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Nonparametric Statistics
Ware, William B.; Althouse, Linda Akel – 1999
This study was designed to derive the distribution of a test statistic based on normal probability plots. The first purpose was to provide an empirical derivation of the critical values for the Line Test (LT) with an extensive computer simulation. The goal was to develop a test that is sensitive to a wide range of alternative distributions,…
Descriptors: Computation, Computer Simulation, Monte Carlo Methods, Probability
Peer reviewedMossholder, Kevin W.; And Others – Educational and Psychological Measurement, 1990
A convention commonly used to describe interaction effects within moderated regression frameworks was examined through logical exposition and a Monte Carlo approach to simulate various moderator conditions. Results, which indicate that the convention may lead to incorrect inferences, are discussed in terms of interpreting moderator effects. (SLD)
Descriptors: Computer Simulation, Data Interpretation, Interaction, Monte Carlo Methods
Peer reviewedBalakrishnan, P. V. (Sunder); And Others – Psychometrika, 1994
A simulation study compares nonhierarchical clustering capabilities of a class of neural networks using Kohonen learning with a K-means clustering procedure. The focus is on the ability of the procedures to recover correctly the known cluster structure in the data. Advantages and disadvantages of the procedures are reviewed. (SLD)
Descriptors: Classification, Cluster Analysis, Comparative Analysis, Computer Simulation
Peer reviewedHuitema, Bradley E.; McKean, Joseph W. – Educational and Psychological Measurement, 1994
Effectiveness of jackknife methods in reducing bias in estimation of the log-1 autocorrelation parameter p1 was evaluated through a Monte Carlo study using sample sizes ranging from 6 to 500. These estimates appear less biased in the small sample case than many that have been investigated recently. (SLD)
Descriptors: Computer Simulation, Estimation (Mathematics), Monte Carlo Methods, Sample Size
Briggs, Derek C.; Wilson, Mark – Journal of Educational Measurement, 2007
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…
Descriptors: Markov Processes, Generalizability Theory, Item Response Theory, Computation
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
Peer reviewedMcCarroll, David; And Others – Educational and Psychological Measurement, 1992
Monte Carlo simulations were used to examine three cases using analyses of variance (ANOVAs) sequentially. Simulation results show that Type I error rates increase when using ANOVAs in this sequential fashion, and the detrimental effect is greatest in situations in which researchers would most likely use ANOVAs sequentially. (SLD)
Descriptors: Analysis of Variance, Computer Simulation, Measurement Techniques, Monte Carlo Methods
Hutchinson, Susan R. – 1994
The work of R. MacCallum et al. (1992) was extended by examining chance modifications through a Monte Carlo simulation. The stability of post hoc model modifications was examined under varying sample size, model complexity, and severity of misspecification using 2- and 4-factor oblique confirmatory factor analysis (CFA) models with four and eight…
Descriptors: Computer Simulation, Models, Monte Carlo Methods, Reliability
PDF pending restorationThompson, Bruce – 1989
In the present study Monte Carlo methods were employed to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. Sampling error influences were investigated across variations in variable and sample (n) sizes, and across variations in average within-set correlation sizes and in…
Descriptors: Computer Simulation, Correlation, Monte Carlo Methods, Multivariate Analysis
Peer reviewedRasmussen, Jeffrey Lee – Multivariate Behavioral Research, 1988
A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Data Analysis, Monte Carlo Methods
Peer reviewedLathrop, Richard G.; Williams, Janice E. – Educational and Psychological Measurement, 1987
A Monte Carlo study, involving 6,000 "computer subjects" and three raters, explored the reliability of the inverse screen test for cluster analysis. Results indicate that the inverse screen may be a useful and reliable cluster analytic technique for determining the number of true groups. (TJH)
Descriptors: Cluster Analysis, Computer Simulation, Interrater Reliability, Monte Carlo Methods
Peer reviewedCohen, Ayala – Psychometrika, 1986
This article proposes a method for testing equality of variances which exploits Pitman's idea and the computational power of simulations. Several advantages to this method are illustrated. A Monte Carlo study for several combinations of sample sizes and number of variables is presented. (Author/LMO)
Descriptors: Analysis of Covariance, Computer Simulation, Correlation, Hypothesis Testing
Peer reviewedOttenbacher, Kenneth J. – Journal of Research and Development in Education, 1989
Simulation studies were used to explore the relationship between Type I error rates (statistical conclusion validity) and multiple testing in data sets exhibiting varying degrees of independence. Implications for reporting and interpreting educational data are discussed, and methods of determining or reducing Type I error incidence are presented.…
Descriptors: Computer Simulation, Educational Research, Monte Carlo Methods, Research Problems
Peer reviewedCohen, Jacob; Nee, John C. M. – Multivariate Behavioral Research, 1990
The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)
Descriptors: Computer Simulation, Monte Carlo Methods, Multivariate Analysis, Power (Statistics)

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