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Chan, Wendy – American Journal of Evaluation, 2022
Over the past ten years, propensity score methods have made an important contribution to improving generalizations from studies that do not select samples randomly from a population of inference. However, these methods require assumptions and recent work has considered the role of bounding approaches that provide a range of treatment impact…
Descriptors: Probability, Scores, Scoring, Generalization
Xiao, Leifeng; Hau, Kit-Tai – Educational and Psychological Measurement, 2023
We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient "H") with continuous and discrete data having different types of non-normality. Results showed the estimation bias was…
Descriptors: Statistical Bias, Statistical Analysis, Likert Scales, Statistical Distributions
Shear, Benjamin R.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2021
This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Sample Size
Nam, Yeji; Hong, Sehee – Educational and Psychological Measurement, 2021
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…
Descriptors: Probability, Models, Statistical Analysis, Statistical Distributions
Shear, Benjamin R.; Reardon, Sean F. – Stanford Center for Education Policy Analysis, 2019
This paper describes a method for pooling grouped, ordered-categorical data across multiple waves to improve small-sample heteroskedastic ordered probit (HETOP) estimates of latent distributional parameters. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in each of a small…
Descriptors: Computation, Scores, Statistical Distributions, Sample Size
Quesen, Sarah – ProQuest LLC, 2016
When studying differential item functioning (DIF) with students with disabilities (SWD) focal groups typically suffer from small sample size, whereas the reference group population is usually large. This makes it possible for a researcher to select a sample from the reference population to be similar to the focal group on the ability scale. Doing…
Descriptors: Test Items, Academic Accommodations (Disabilities), Testing Accommodations, Disabilities
Oh, Hyeonjoo J.; Guo, Hongwen; Walker, Michael E. – ETS Research Report Series, 2009
Issues of equity and fairness across subgroups of the population (e.g., gender or ethnicity) must be seriously considered in any standardized testing program. For this reason, many testing programs require some means for assessing test characteristics, such as reliability, for subgroups of the population. However, often only small sample sizes are…
Descriptors: Standardized Tests, Test Reliability, Sample Size, Bayesian Statistics
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research

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

Zeng, Lingjia; Cope, Ronald T. – Journal of Educational and Behavioral Statistics, 1995
Large-sample standard errors of linear equating for the counterbalanced design are derived using the general delta method. Computer simulations found that standard errors derived without the normality assumption were more accurate than those derived with the normality assumption in a large sample with moderately skewed score distributions. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Research Design, Sample Size
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)
Pommerich, Mary; And Others – 1994
The functioning of two population-based Mantel-Haenszel (MH) common-odds ratios was compared. One ratio is conditioned on the observed test score, while the other is conditioned on a latent trait or true ability score. When the comparison group distributions are incongruent or nonoverlapping to some degree, the observed score represents different…
Descriptors: Ability, Comparative Analysis, Item Bias, Performance