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Elliott, Mark; Buttery, Paula – Educational and Psychological Measurement, 2022
We investigate two non-iterative estimation procedures for Rasch models, the pair-wise estimation procedure (PAIR) and the Eigenvector method (EVM), and identify theoretical issues with EVM for rating scale model (RSM) threshold estimation. We develop a new procedure to resolve these issues--the conditional pairwise adjacent thresholds procedure…
Descriptors: Item Response Theory, Rating Scales, Computation, Simulation
Wiens, Stefan; Nilsson, Mats E. – Educational and Psychological Measurement, 2017
Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…
Descriptors: Data Analysis, Effect Size, Computation, Statistical Analysis
Trafimow, David – Educational and Psychological Measurement, 2018
Because error variance alternatively can be considered to be the sum of systematic variance associated with unknown variables and randomness, a tripartite assumption is proposed that total variance in the dependent variable can be partitioned into three variance components. These are variance in the dependent variable that is explained by the…
Descriptors: Statistical Analysis, Correlation, Experiments, Effect Size
Wilcox, Rand R.; Serang, Sarfaraz – Educational and Psychological Measurement, 2017
The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…
Descriptors: Hypothesis Testing, Bayesian Statistics, Computation, Effect Size
DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
García-Pérez, Miguel A. – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…
Descriptors: Hypothesis Testing, Statistical Inference, Effect Size, Bayesian Statistics
Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2017
Field experiments in education frequently assign entire groups such as schools to treatment or control conditions. These experiments incorporate sometimes a longitudinal component where for example students are followed over time to assess differences in the average rate of linear change, or rate of acceleration. In this study, we provide methods…
Descriptors: Educational Experiments, Field Studies, Models, Randomized Controlled Trials
Finch, W. Holmes; French, Brian F. – Educational and Psychological Measurement, 2012
Effect size use has been increasing in the past decade in many research areas. Confidence intervals associated with effect sizes are encouraged to be reported. Prior work has investigated the performance of confidence interval estimation with Cohen's d. This study extends this line of work to the analysis of variance case with more than two…
Descriptors: Computation, Statistical Analysis, Effect Size, Comparative Analysis
Ye, Meng; Xin, Tao – Educational and Psychological Measurement, 2014
The authors explored the effects of drifting common items on vertical scaling within the higher order framework of item parameter drift (IPD). The results showed that if IPD occurred between a pair of test levels, the scaling performance started to deviate from the ideal state, as indicated by bias of scaling. When there were two items drifting…
Descriptors: Scaling, Test Items, Equated Scores, Achievement Gains
Walker, Cindy M.; Zhang, Bo; Banks, Kathleen; Cappaert, Kevin – Educational and Psychological Measurement, 2012
The purpose of this simulation study was to establish general effect size guidelines for interpreting the results of differential bundle functioning (DBF) analyses using simultaneous item bias test (SIBTEST). Three factors were manipulated: number of items in a bundle, test length, and magnitude of uniform differential item functioning (DIF)…
Descriptors: Test Bias, Test Length, Simulation, Guidelines
Le, Huy; Marcus, Justin – Educational and Psychological Measurement, 2012
This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…
Descriptors: Monte Carlo Methods, Probability, Mathematical Concepts, Effect Size
Hoekstra, Rink; Johnson, Addie; Kiers, Henk A. L. – Educational and Psychological Measurement, 2012
The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the…
Descriptors: Computation, Statistical Analysis, Hypothesis Testing, Statistical Significance
Marin-Martinez, Fulgencio; Sanchez-Meca, Julio – Educational and Psychological Measurement, 2010
Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…
Descriptors: Meta Analysis, Sample Size, Effect Size, Monte Carlo Methods
Carvajal, Jorge; Skorupski, William P. – Educational and Psychological Measurement, 2010
This study is an evaluation of the behavior of the Liu-Agresti estimator of the cumulative common odds ratio when identifying differential item functioning (DIF) with polytomously scored test items using small samples. The Liu-Agresti estimator has been proposed by Penfield and Algina as a promising approach for the study of polytomous DIF but no…
Descriptors: Test Bias, Sample Size, Test Items, Computation
Crede, Marcus – Educational and Psychological Measurement, 2010
Random responding to psychological inventories is a long-standing concern among clinical practitioners and researchers interested in interpreting idiographic data, but it is typically viewed as having only a minor impact on the statistical inferences drawn from nomothetic data. This article explores the impact of random responding on the size and…
Descriptors: Effect Size, Validity, Computation, Correlation
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