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Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2016
This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…
Descriptors: Sample Size, Interaction, Statistical Analysis, Sampling
Sirakaya, Mustafa; Alsancak Sirakaya, Didem – Malaysian Online Journal of Educational Technology, 2018
This study aimed to identify the trends in the studies conducted on Educational Augmented Reality (AR). 105 articles found in ERIC, EBSCOhost and ScienceDirect databases were reviewed with this purpose in mind. Analyses displayed that the number of educational AR studies has increased over the years. Quantitative methods were mostly preferred in…
Descriptors: Simulated Environment, Teaching Methods, Literature Reviews, Research Methodology
Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2015
Paired-samples designs are used frequently in educational and behavioral research. In applications where the response variable is quantitative, researchers are encouraged to supplement the results of a paired-samples t-test with a confidence interval (CI) for a mean difference or a standardized mean difference. Six CIs for standardized mean…
Descriptors: Educational Research, Sample Size, Statistical Analysis, Effect Size
Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2011
Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…
Descriptors: Sample Size, Monte Carlo Methods, Statistical Analysis, Heterogeneous Grouping
Kubinger, Klaus D.; Rasch, Dieter; Yanagida, Takuya – Educational Research and Evaluation, 2011
Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and…
Descriptors: Sample Size, Simulation, Testing, Achievement Tests
Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng – Journal of Experimental Education, 2008
Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…
Descriptors: Sample Size, Computer Simulation, Statistical Analysis, Tests
Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
Fidalgo, Angel M.; Hashimoto, Kanako; Bartram, Dave; Muniz, Jose – Journal of Experimental Education, 2007
In this study, the authors assess several strategies created on the basis of the Mantel-Haenszel (MH) procedure for conducting differential item functioning (DIF) analysis with small samples. One of the analytical strategies is a loss function (LF) that uses empirical Bayes Mantel-Haenszel estimators, whereas the other strategies use the classical…
Descriptors: Bayesian Statistics, Test Bias, Statistical Analysis, Sample Size
Spray, Judith; Miller, Tim – 1994
Computer simulations under three conditions of polytomous differential item functioning (DIF) compared the ability of three different statistical procedures to detect nonuniform DIF. The procedures were a nominal and an ordinal extension of the Mantel-Haenszel statistic, and logistic discriminant function analysis. Results showed that only the…
Descriptors: Computer Simulation, Identification, Item Bias, Sample Size
Houts, Lisa M.; Taylor, James C. – Journal of College Teaching & Learning, 2008
The production and operations management class offered at California State University, Fresno underwent a transformation from being a four-unit, face-to-face course to a hybrid course. This hybrid course, which is required for all students in the Craig School of Business, includes two units of face-to-face instruction each week, with some coverage…
Descriptors: Grades (Scholastic), Academic Achievement, College Students, Blended Learning
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
Peer reviewedLathrop, Richard G.; Williams, Janice E. – Educational and Psychological Measurement, 1989
A Monte Carlo study determined the Inverse Scree Test's shape with various numbers of true groups and under different conditions of distribution shape and sample size. Six simulated distributions of 3,000 subjects each and 1 with 1,500 were created. Findings suggest relative distribution independence, number independence, and modest…
Descriptors: Cluster Analysis, Computer Simulation, Factor Analysis, Graphs
Peer reviewedWilcox, Rand R.; Charlin, Ventura L. – Journal of Educational Statistics, 1986
This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)
Tryon, Warren W. – 1984
A normally distributed data set of 1,000 values--ranging from 50 to 150, with a mean of 50 and a standard deviation of 20--was created in order to evaluate the bootstrap method of repeated random sampling. Nine bootstrap samples of N=10 and nine more bootstrap samples of N=25 were randomly selected. One thousand random samples were selected from…
Descriptors: Computer Simulation, Estimation (Mathematics), Higher Education, Monte Carlo Methods
Oil and Gas on Indian Reservations: Statistical Methods Help to Establish Value for Royalty Purposes
Fowler, Mary S.; Kadane, Joseph B. – Journal of Statistics Education, 2006
Part of the history of oil and gas development on Indian reservations concerns potential underpayment of royalties due to under-valuation of production by oil companies. This paper discusses a model used by the Shoshone and Arapaho tribes in a lawsuit against the Federal government, claiming the Government failed to collect adequate royalties.…
Descriptors: Fuels, American Indian Education, Federal Government, Probability

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