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Showing all 11 results Save | Export
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Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
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Shieh, Gwowen – Journal of Experimental Education, 2019
The analysis of covariance (ANCOVA) is a useful statistical procedure that incorporates covariate features into the adjustment of treatment effects. The consequences of omitted prognostic covariates on the statistical inferences of ANCOVA are well documented in the literature. However, the corresponding influence on sample-size calculations for…
Descriptors: Sample Size, Statistical Analysis, Computation, Accuracy
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Liu, Yang; Yang, Ji Seung – Journal of Educational and Behavioral Statistics, 2018
The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…
Descriptors: Intervals, Scores, Item Response Theory, Bayesian Statistics
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Swire, Briony; Ecker, Ullrich K. H.; Lewandowsky, Stephan – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
People frequently continue to use inaccurate information in their reasoning even after a credible retraction has been presented. This phenomenon is often referred to as the continued influence effect of misinformation. The repetition of the original misconception within a retraction could contribute to this phenomenon, as it could inadvertently…
Descriptors: Information Utilization, Familiarity, Error Correction, Misconceptions
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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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Laumakis, Paul – Mathematics Teacher, 2011
When taking mathematics courses, students will sometimes ask their recurring question, "When will I ever use this in real life?" Educators are often unable to provide a direct connection between what they are teaching in the classroom and a real-life application. However, when such an opportunity does arise, they should seize it and…
Descriptors: Regression (Statistics), Mathematics Instruction, Mathematics, Mathematics Curriculum
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LeMire, Steven D. – Journal of Statistics Education, 2010
This paper proposes an argument framework for the teaching of null hypothesis statistical testing and its application in support of research. Elements of the Toulmin (1958) model of argument are used to illustrate the use of p values and Type I and Type II error rates in support of claims about statistical parameters and subject matter research…
Descriptors: Hypothesis Testing, Relationship, Statistical Significance, Models
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Byrd, Jimmy; Eddy, Colleen – Journal of Educational Administration, 2009
Purpose: The purpose of this study was to review research published by "Journal of Educational Administration (JEA)" and the "Educational Administration Quarterly (EAQ)" over the past ten years to examine the type of research reported and to determine if confidence intervals and effect sizes were being reported as recommended by the American…
Descriptors: Educational Administration, Periodicals, Journal Articles, Educational Research
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research
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Byrd, Jimmy K. – Educational Administration Quarterly, 2007
Purpose: The purpose of this study was to review research published by Educational Administration Quarterly (EAQ) during the past 10 years to determine if confidence intervals and effect sizes were being reported as recommended by the American Psychological Association (APA) Publication Manual. Research Design: The author examined 49 volumes of…
Descriptors: Research Design, Intervals, Statistical Inference, Effect Size
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Ozgur, Ceyhun; Strasser, Sandra E. – Decision Sciences Journal of Innovative Education, 2004
Authors who write introductory business statistics texts do not agree on when to use a t distribution and when to use a Z distribution in both the construction of confidence intervals and the use of hypothesis testing. In a survey of textbooks written in the last 15 years, we found the decision rules to be contradictory and, at times, the…
Descriptors: Statistics, Statistical Analysis, Textbooks, Textbook Evaluation