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Ponce-Renova, Hector F. – Journal of New Approaches in Educational Research, 2022
This paper's objective was to teach the Equivalence Testing applied to Educational Research to emphasize recommendations and to increase quality of research. Equivalence Testing is a technique used to compare effect sizes or means of two different studies to ascertain if they would be statistically equivalent. For making accessible Equivalence…
Descriptors: Educational Research, Effect Size, Statistical Analysis, Intervals
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Dimitrov, Dimiter M. – Measurement and Evaluation in Counseling and Development, 2017
This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.
Descriptors: Test Bias, Item Response Theory, Factor Analysis, Evaluation Methods
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Jackson, Dan; Bowden, Jack; Baker, Rose – Research Synthesis Methods, 2015
Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Computation, Evaluation Methods
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Shieh, Gwowen – Journal of Experimental Education, 2015
Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…
Descriptors: Statistical Analysis, Sample Size, Computation, Effect Size
Williams, Ryan T. – ProQuest LLC, 2012
Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…
Descriptors: Multiple Regression Analysis, Meta Analysis, Evaluation Methods, Computation
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Padilla, Miguel A.; Divers, Jasmin; Newton, Matthew – Applied Psychological Measurement, 2012
Three different bootstrap methods for estimating confidence intervals (CIs) for coefficient alpha were investigated. In addition, the bootstrap methods were compared with the most promising coefficient alpha CI estimation methods reported in the literature. The CI methods were assessed through a Monte Carlo simulation utilizing conditions…
Descriptors: Intervals, Monte Carlo Methods, Computation, Sampling
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Romano, Jeanine L.; Kromrey, Jeffrey D.; Owens, Corina M.; Scott, Heather M. – Journal of Experimental Education, 2011
In this study, the authors aimed to examine 8 of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions wherein the underlying item…
Descriptors: Intervals, Monte Carlo Methods, Rating Scales, Computation
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Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M. – Applied Psychological Measurement, 2011
Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…
Descriptors: Intervals, Item Response Theory, Models, Evaluation Methods
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Sass, Daniel A. – Educational and Psychological Measurement, 2010
Exploratory factor analysis (EFA) is commonly employed to evaluate the factor structure of measures with dichotomously scored items. Generally, only the estimated factor loadings are provided with no reference to significance tests, confidence intervals, and/or estimated factor loading standard errors. This simulation study assessed factor loading…
Descriptors: Intervals, Simulation, Factor Structure, Hypothesis Testing
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Lee, Chun-Ting; Zhang, Guangjian; Edwards, Michael C. – Multivariate Behavioral Research, 2012
Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable.…
Descriptors: Personality Traits, Intervals, Monte Carlo Methods, Factor Analysis
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Zientek, Linda Reichwein; Ozel, Z. Ebrar Yetkiner; Ozel, Serkan; Allen, Jeff – Career and Technical Education Research, 2012
Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…
Descriptors: Vocational Education, Effect Size, Intervals, Self Esteem
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Shiyko, Mariya P.; Ram, Nilam – Multivariate Behavioral Research, 2011
Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread,…
Descriptors: Generalizability Theory, Intervals, Smoking, Self Efficacy
Feng, Xingdong – ProQuest LLC, 2009
Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…
Descriptors: Intervals, Computation, Genetics, Data Analysis
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Choi, Jaehwa; Fan, Weihua; Hancock, Gregory R. – Multivariate Behavioral Research, 2009
This note suggests delta method implementations for deriving confidence intervals for a latent mean effect size measure for the case of 2 independent populations. A hypothetical kindergarten reading example using these implementations is provided, as is supporting LISREL syntax. (Contains 1 table.)
Descriptors: Intervals, Syntax, Effect Size, Evaluation Methods
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Alvero, Alicia M.; Struss, Kristen; Rappaport, Eva – Journal of Organizational Behavior Management, 2008
Partial-interval (PIR), whole-interval (WIR), and momentary time sampling (MTS) estimates were compared against continuous measures of safety performance for three postural behaviors: feet, back, and shoulder position. Twenty-five samples of safety performance across five undergraduate students were scored using a second-by-second continuous…
Descriptors: Undergraduate Students, Intervals, Safety, Drinking
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