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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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Adler, Moshe – Education Policy Analysis Archives, 2013
The authors of the study "The Long-Term Impact of Teachers" claim that their study shows that increases in teacher value-added lead to significant and lasting increases in test scores and significant increases in income that will last throughout adulthood. Instead, I show that these claims are false because they are contradicted by the…
Descriptors: Teacher Effectiveness, Academic Achievement, Income, Scores
Kotrlik, Joe W.; Williams, Heather A.; Jabor, M. Khata – Journal of Agricultural Education, 2011
The Journal of Agricultural Education (JAE) requires authors to follow the guidelines stated in the Publication Manual of the American Psychological Association [APA] (2009) in preparing research manuscripts, and to utilize accepted research and statistical methods in conducting quantitative research studies. The APA recommends the reporting of…
Descriptors: Agricultural Education, Statistical Significance, Effect Size, Educational Research
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Sun, Shuyan; Pan, Wei; Wang, Lihshing Leigh – Journal of Educational Psychology, 2010
Null hypothesis significance testing has dominated quantitative research in education and psychology. However, the statistical significance of a test as indicated by a p-value does not speak to the practical significance of the study. Thus, reporting effect size to supplement p-value is highly recommended by scholars, journal editors, and academic…
Descriptors: Effect Size, Statistical Inference, Statistical Significance, Data Interpretation
Barcikowski, Robert; Robey, Randall R. – 1990
Use of "special" orthonormal mean contrasts and mean contrast variances can help educational researchers interpret a wide variety of repeated measures data. Most statistical packages allow educational researchers to test for differences across repeated measures using both the univariate mixed model F test and a multivariate test.…
Descriptors: Computer Software, Data Interpretation, Educational Research, Equations (Mathematics)
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Vacha-Haase, Tammi; Nilsson, Johanna E. – Measurement and Evaluation in Counseling and Development, 1998
Statistical significance reporting and use in educational and psychological research is reviewed. An assessment of the use of statistical significance in articles published in MECD from 1990-1996 is presented. The elements of statistical significance (including sample size, effect size, and power), interpretation of results, common erroneous…
Descriptors: Data Interpretation, Educational Research, Hypothesis Testing, Measurement
Moore, Mary Ann – 1991
This paper examines the problems caused by relying solely on statistical significance tests to interpret results in contemporary social science. The place of significance testing in educational research has often been debated. Among the problems in reporting statistical significance are questions of definition and terminology. Problems are also…
Descriptors: Data Interpretation, Educational Research, Effect Size, Research Methodology
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Knapp, Thomas R. – Mid-Western Educational Researcher, 1999
Presents an opinion on the appropriate use of significance tests, especially in the context of regression analysis, the most commonly encountered statistical technique in education and related disciplines. Briefly discusses the appropriate use of power analysis. Contains 47 references. (Author/SV)
Descriptors: Data Interpretation, Educational Research, Effect Size, Hypothesis Testing
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Azevedo, Roger; Bernard, Robert – British Journal of Educational Technology, 1995
A meta-analysis determined the importance of feedback in computer-based learning; 59 studies were collected and evaluated for inclusion in the meta-analysis in terms of design, sample size, and availability of appropriate statistics. Achievement outcomes were found to be greater for the feedback group than the control group. (AEF)
Descriptors: Achievement Rating, Computer Assisted Instruction, Data Interpretation, Educational Research