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Showing 1 to 15 of 276 results Save | Export
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Michael Borenstein – Research Synthesis Methods, 2024
In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…
Descriptors: Meta Analysis, Error Patterns, Statistical Analysis, Intervention
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Li, Dongmei – Journal of Educational Measurement, 2022
Equating error is usually small relative to the magnitude of measurement error, but it could be one of the major sources of error contributing to mean scores of large groups in educational measurement, such as the year-to-year state mean score fluctuations. Though testing programs may routinely calculate the standard error of equating (SEE), the…
Descriptors: Error Patterns, Educational Testing, Group Testing, Statistical Analysis
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Babcock, Ben; Marks, Peter E. L.; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2022
A wide variety of methodological choices and situations can affect the quality of peer nomination measurements but have not received adequate study. This article begins by focusing on systematic nominator missingness as an example of one such situation. We reanalyzed findings from a recent study by Bukowski, Dirks, Commisso, Velàsquez, and Lopez…
Descriptors: Research Methodology, Peer Relationship, Statistical Analysis, Error Patterns
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Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).
Descriptors: Statistical Analysis, Goodness of Fit, Factor Analysis, Structural Equation Models
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Warne, Russell T. – Journal of Advanced Academics, 2022
Recently, Picho-Kiroga (2021) published a meta-analysis on the effect of stereotype threat on females. Their conclusion was that the average effect size for stereotype threat studies was d = .28, but that effects are overstated because the majority of studies on stereotype threat in females include methodological characteristics that inflate the…
Descriptors: Sex Stereotypes, Females, Meta Analysis, Effect Size
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Berrío, Ángela I.; Herrera, Aura N.; Gómez-Benito, Juana – Journal of Experimental Education, 2019
This study examined the effect of sample size ratio and model misfit on the Type I error rates and power of the Difficulty Parameter Differences procedure using Winsteps. A unidimensional 30-item test with responses from 130,000 examinees was simulated and four independent variables were manipulated: sample size ratio (20/100/250/500/1000); model…
Descriptors: Sample Size, Test Bias, Goodness of Fit, Statistical Analysis
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Park, Sunyoung; Beretvas, S. Natasha – Journal of Experimental Education, 2019
The log-odds ratio (ln[OR]) is commonly used to quantify treatments' effects on dichotomous outcomes and then pooled across studies using inverse-variance (1/v) weights. Calculation of the ln[OR]'s variance requires four cell frequencies for two groups crossed with values for dichotomous outcomes. While primary studies report the total sample size…
Descriptors: Sample Size, Meta Analysis, Statistical Analysis, Efficiency
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Coleman, Aaron B.; Lorenzo, Kyla; McLamb, Flannery; Sanku, Abhiraj; Khan, Sahil; Bozinovic, Goran – Biochemistry and Molecular Biology Education, 2023
Effectively teaching scientific reasoning requires an understanding of the challenges students face when learning these skills. We designed an assessment that measures undergraduate student abilities to form hypotheses, design experiments, and interpret data from experiments in cellular and molecular biology. The assessment uses…
Descriptors: Logical Thinking, Science Process Skills, Undergraduate Students, Cytology
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Yang, Shitao; Black, Ken – Teaching Statistics: An International Journal for Teachers, 2019
Summary Employing a Wald confidence interval to test hypotheses about population proportions could lead to an increase in Type I or Type II errors unless the hypothesized value, p0, is used in computing its standard error rather than the sample proportion. Whereas the Wald confidence interval to estimate a population proportion uses the sample…
Descriptors: Error Patterns, Evaluation Methods, Error of Measurement, Measurement Techniques
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Onwuegbuzie, Anthony J. – Journal of Educational Issues, 2018
Evidence has been provided about the importance of avoiding American Psychological Association (APA) errors in the abstract, body, reference list, and table sections of empirical research articles. Specifically, authors are significantly more likely to have their manuscripts rejected for publication if they fail to avoid APA violations--and, thus,…
Descriptors: Literature Reviews, Journal Articles, Communication Problems, Authors
Almoied, Ayed – ProQuest LLC, 2017
Classical statistical tests are used in many disciplines such as education and psychology. Such tests are based on certain assumptions (e.g., normality and homoscedasticity) that are must to be met in order to produce accurate results. Violation of such assumptions is a common problem researchers encounter, particularly when analyzing real data.…
Descriptors: Evaluation, Statistical Analysis, Evaluation Methods, Simulation
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Clawson, Ann; South, Mikle; Baldwin, Scott A.; Larson, Michael J. – Journal of Autism and Developmental Disorders, 2017
We examined the error-related negativity (ERN) as an endophenotype of ASD by comparing the ERN in families of ASD probands to control families. We hypothesized that ASD probands and families would display reduced-amplitude ERN relative to controls. Participants included 148 individuals within 39 families consisting of a mother, father, sibling,…
Descriptors: Pervasive Developmental Disorders, Autism, Statistical Analysis, Multiple Regression Analysis
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von Davier, Matthias – Quality Assurance in Education: An International Perspective, 2018
Purpose: Surveys that include skill measures may suffer from additional sources of error compared to those containing questionnaires alone. Examples are distractions such as noise or interruptions of testing sessions, as well as fatigue or lack of motivation to succeed. This paper aims to provide a review of statistical tools based on latent…
Descriptors: Statistical Analysis, Surveys, International Assessment, Error Patterns
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
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Xie, Zilong; Reetzke, Rachel; Chandrasekaran, Bharath – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Speech-evoked neurophysiological responses are often collected to answer clinically and theoretically driven questions concerning speech and language processing. Here, we highlight the practical application of machine learning (ML)-based approaches to analyzing speech-evoked neurophysiological responses. Method: Two categories of ML-based…
Descriptors: Speech Language Pathology, Intervention, Communication Problems, Speech Impairments
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