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Tong, Xin; Zhang, Zhiyong – Grantee Submission, 2020
Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…
Descriptors: Robustness (Statistics), Bayesian Statistics, Models, Error of Measurement
Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2017
Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…
Descriptors: Scores, Statistical Analysis, Models, Computation
Kulick, George; Wright, Ronald – International Journal for the Scholarship of Teaching and Learning, 2008
Grading on the curve is a common practice in higher education. While there are many critics of the practice it still finds wide spread acceptance particularly in science classes. Advocates believe that in large classes student ability is likely to be normally distributed. If test scores are also normally distributed instructors and students tend…
Descriptors: Grading, Higher Education, Scores, Outcomes of Education

Harwell, 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
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
Harwell, Michael – 1995
The test of homogeneity developed by L. V. Hedges (1982) for the fixed effects model is frequently used in quantitative meta-analyses to test whether effect sizes are equal. Despite its widespread use, evidence of the behavior of this test for the less-than-ideal case of small study sample sizes paired with large numbers of studies is…
Descriptors: Effect Size, Meta Analysis, Monte Carlo Methods, Power (Statistics)

You, Soon-Hyung; Stone-Romero, Eugene F. – Educational and Psychological Measurement, 1996
To clarify the findings of R. Gillett (1991) about the inequality of the means of test scores of minority and majority examinees, the standard errors of the quota-selected sample means and the sampling distribution of these means were studied through Monte Carlo simulation. Results explain that the quota selection inequality results from…
Descriptors: Error of Measurement, Minority Groups, Monte Carlo Methods, Sampling

Sijtsma, Klaas; Molenaar, Ivo W. – Psychometrika, 1987
Three methods for estimating reliability are studied within the context of nonparametric item response theory. Two were proposed originally by Mokken and a third is developed in this paper. Using a Monte Carlo strategy, these three estimation methods are compared with four "classical" lower bounds to reliability. (Author/JAZ)
Descriptors: Estimation (Mathematics), Latent Trait Theory, Measurement Techniques, Monte Carlo Methods

Fowler, Robert L.; Clingman, Joy M. – Educational and Psychological Measurement, 1992
Monte Carlo techniques are used to examine the power of the "B" statistic of R. L. Brennan (1972) to detect negatively discriminating items drawn from a variety of nonnormal population distributions. A simplified procedure is offered for conducting an item-discrimination analysis on typical classroom objective tests. (SLD)
Descriptors: Classroom Techniques, Elementary Secondary Education, Equations (Mathematics), Item Analysis