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Showing 1 to 15 of 34 results Save | Export
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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
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Pustejovsky, James E.; Rodgers, Melissa A. – Research Synthesis Methods, 2019
Publication bias and other forms of outcome reporting bias are critical threats to the validity of findings from research syntheses. A variety of methods have been proposed for detecting selective outcome reporting in a collection of effect size estimates, including several methods based on assessment of asymmetry of funnel plots, such as the…
Descriptors: Effect Size, Regression (Statistics), Statistical Analysis, Error of Measurement
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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
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Debray, Thomas P. A.; Moons, Karel G. M.; Riley, Richard D. – Research Synthesis Methods, 2018
Small-study effects are a common threat in systematic reviews and may indicate publication bias. Their existence is often verified by visual inspection of the funnel plot. Formal tests to assess the presence of funnel plot asymmetry typically estimate the association between the reported effect size and their standard error, the total sample size,…
Descriptors: Meta Analysis, Comparative Analysis, Publications, Bias
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Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
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Weller, Susan C. – Field Methods, 2015
This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…
Descriptors: Sample Size, Statistical Analysis, Computation, Hypothesis Testing
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Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
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Ing, Marsha; Victorino, Christine – Journal of Engineering Education, 2016
Background: Asian American experiences have been largely ignored in the engineering education research literature. Asian Americans are often considered as a homogenous group, despite including over 40 different ethnic subgroups who speak over 300 languages. The immigrant trajectories, cultural experiences, and college completion rates of Asian…
Descriptors: Asian Americans, Learner Engagement, Engineering Education, Undergraduate Students
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Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon – Educational and Psychological Measurement, 2014
Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (?) of the studied item was the same as the ? of the total score. The current study extended…
Descriptors: Test Bias, Correlation, Scores, Comparative Analysis
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Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2016
Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…
Descriptors: Educational Experiments, Error of Measurement, Research Design, Statistical Analysis
Topczewski, Anna Marie – ProQuest LLC, 2013
Developmental score scales represent the performance of students along a continuum, where as students learn more they move higher along that continuum. Unidimensional item response theory (UIRT) vertical scaling has become a commonly used method to create developmental score scales. Research has shown that UIRT vertical scaling methods can be…
Descriptors: Item Response Theory, Scaling, Scores, Student Development
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Asil, Mustafa; Brown, Gavin T. L. – International Journal of Testing, 2016
The use of the Programme for International Student Assessment (PISA) across nations, cultures, and languages has been criticized. The key criticisms point to the linguistic and cultural biases potentially underlying the design of reading comprehension tests, raising doubts about the legitimacy of comparisons across economies. Our research focused…
Descriptors: Comparative Analysis, Reading Achievement, Achievement Tests, Secondary School Students
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Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2011
Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…
Descriptors: Effect Size, Research Design, Experiments, Computation
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Onwuegbuzie, Anthony J.; Levin, Joel R.; Ferron, John M. – Journal of Experimental Education, 2011
Building on previous arguments for why educational researchers should not provide effect-size estimates in the face of statistically nonsignificant outcomes (Robinson & Levin, 1997), Onwuegbuzie and Levin (2005) proposed a 3-step statistical approach for assessing group differences when multiple outcome measures are individually analyzed…
Descriptors: Hypothesis Testing, Statistical Analysis, Effect Size, Probability
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