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Maryellen Brunson McClain; Tiffany L. Otero; Jillian Haut; Rochelle B. Schatz – Sage Research Methods Cases, 2014
With growing popularity of single subject design as a method to evaluate the efficacy of interventions, it is important to ensure that the analyses of these methods are rigorous and reliable. The purpose of this case study is to discuss the measures used to evaluate the efficacy of interventions in single subject design studies in the fields of…
Descriptors: Educational Research, Effect Size, Data Analysis, Data Interpretation
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Drummond, Gordon B.; Tom, Brian D. M. – Advances in Physiology Education, 2011
In this article, the authors address the practicalities of how data should be presented, summarized, and interpreted. There are no exact rules; indeed there are valid concerns that exact rules may be inappropriate and too prescriptive. New procedures evolve, and new methods may be needed to deal with new types of data, just as people know that new…
Descriptors: Research Methodology, Data Interpretation, Sample Size, Intervals
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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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Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2011
Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…
Descriptors: Educational Research, Statistical Inference, Data Interpretation, Probability
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Chen, Pu-Shih Daniel; Gonyea, Robert M.; Sarraf, Shimon A.; BrckaLorenz, Allison; Korkmaz, Ali; Lambert, Amber D.; Shoup, Rick; Williams, Julie M. – New Directions for Institutional Research, 2009
Colleges and universities in the United States are being challenged to assess student outcomes and the quality of programs and services. One of the more widely used sources of evidence is student engagement as measured by a cluster of student engagement surveys administered by the Center for Postsecondary Research at Indiana University. They…
Descriptors: Data Analysis, Data Interpretation, National Surveys, College Students
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Paris, Scott G.; Luo, Serena Wenshu – Educational Researcher, 2010
The National Early Literacy Panel (2008) report identified early predictors of reading achievement as good targets for instruction, and many of those skills are related to decoding. In this article, the authors suggest that the developmental trajectories of rapidly developing skills pose problems for traditional statistical analyses. Rapidly…
Descriptors: Reading Achievement, Effect Size, Emergent Literacy, Data Interpretation
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Vacha-Haase, Tammi; Thompson, Bruce – Journal of Counseling Psychology, 2004
The present article presents a tutorial on how to estimate and interpret various effect sizes. The 5th edition of the Publication Manual of the American Psychological Association (2001) described the failure to report effect sizes as a "defect" (p. 5), and 23 journals have published author guidelines requiring effect size reporting. Although…
Descriptors: Effect Size, Research Methodology, Computation, Data Interpretation
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McNeil, Keith; Newman, Isadore – Mid-Western Educational Researcher, 1994
Meta-analysis synthesizes related research by considering three major factors: sample size, magnitude of significance, and statistical test used. These factors produce an effect size, expressed as a correlation or as a difference between means, divided by the standard deviation. Discusses ways to use effect size when results are not consistent and…
Descriptors: Data Interpretation, Effect Size, Literature Reviews, Meta Analysis
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Beretvas, S. Natasha – School Psychology Quarterly, 2005
This paper details the challenges encountered by authors summarizing evidence from a primary study to describe a treatment's effectiveness using an effect size (ES) estimate. Dilemmas that are encountered, including how to calculate and interpret the pertinent standardized mean difference ES for results from studies of various research designs,…
Descriptors: Effect Size, Research Methodology, Computation, Data Interpretation