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Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, Error of Measurement
Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size
Raykov, Tenko; DiStefano, Christine; Calvocoressi, Lisa; Volker, Martin – Educational and Psychological Measurement, 2022
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free…
Descriptors: Effect Size, Models, Measurement Techniques, Factor Analysis
Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
Lin, Lifeng – Research Synthesis Methods, 2019
Assessing publication bias is a critical procedure in meta-analyses for rating the synthesized overall evidence. Because statistical tests for publication bias are usually not powerful and only give "P" values that inform either the presence or absence of the bias, examining the asymmetry of funnel plots has been popular to investigate…
Descriptors: Meta Analysis, Sample Size, Graphs, Bias
Koziol, Natalie A.; Goodrich, J. Marc; Yoon, HyeonJin – Educational and Psychological Measurement, 2022
Differential item functioning (DIF) is often used to examine validity evidence of alternate form test accommodations. Unfortunately, traditional approaches for evaluating DIF are prone to selection bias. This article proposes a novel DIF framework that capitalizes on regression discontinuity design analysis to control for selection bias. A…
Descriptors: Regression (Statistics), Item Analysis, Validity, Testing Accommodations
Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Hong, Sanghyun; Reed, W. Robert – Research Synthesis Methods, 2021
The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…
Descriptors: Monte Carlo Methods, Meta Analysis, Research Methodology, Experiments
Park, Sung Eun; Ahn, Soyeon; Zopluoglu, Cengiz – Educational and Psychological Measurement, 2021
This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across…
Descriptors: Item Analysis, Effect Size, Difficulty Level, Monte Carlo Methods
Smith, Kendal N.; Lamb, Kristen N.; Henson, Robin K. – Gifted Child Quarterly, 2020
Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…
Descriptors: Multivariate Analysis, Academically Gifted, Gifted Education, Educational Research
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
Joo, Seang-hwane; Wang, Yan; Ferron, John M. – AERA Online Paper Repository, 2017
Multiple-baseline studies provide meta-analysts the opportunity to compute effect sizes based on either within-series comparisons of treatment phase to baseline phase observations, or time specific between-series comparisons of observations from those that have started treatment to observations of those that are still in baseline. The advantage of…
Descriptors: Meta Analysis, Effect Size, Hierarchical Linear Modeling, Computation
Cao, Mengyang; Tay, Louis; Liu, Yaowu – Educational and Psychological Measurement, 2017
This study examined the performance of a proposed iterative Wald approach for detecting differential item functioning (DIF) between two groups when preknowledge of anchor items is absent. The iterative approach utilizes the Wald-2 approach to identify anchor items and then iteratively tests for DIF items with the Wald-1 approach. Monte Carlo…
Descriptors: Monte Carlo Methods, Test Items, Test Bias, Error of Measurement
Kelcey, Benjamin; Dong, Nianbo; Spybrook, Jessaca; Cox, Kyle – Journal of Educational and Behavioral Statistics, 2017
Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement "what works" questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Mediation Theory, Models
Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun – Grantee Submission, 2017
The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…
Descriptors: Statistical Analysis, Evaluation Methods, Structural Equation Models, Reliability