2012
DOI: 10.1177/0016986212444122
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Statistical Methods Used in Gifted Education Journals, 2006-2010

Abstract: This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson's r (47.8%), χ 2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach's alpha was the most commonly reported m… Show more

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Cited by 44 publications
(46 citation statements)
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“…This is particularly true for long‐term programs that require extensive investments of time . When talented girls participate in such extracurricular programs, little can be concluded about the programs’ effectiveness, as control groups are often missing or inappropriately designed …”
Section: Females In Stemmentioning
confidence: 99%
“…This is particularly true for long‐term programs that require extensive investments of time . When talented girls participate in such extracurricular programs, little can be concluded about the programs’ effectiveness, as control groups are often missing or inappropriately designed …”
Section: Females In Stemmentioning
confidence: 99%
“…Kramer-Welch test was set for uniform groups studied parameters. Indeed, after the first month of therapy results were statistically indistinguishable (p = 0.049), but after three months difference reached statistical significance for parameters such as the volume (p = 0.00088) and the number of nocturnal enuresis (p = 0.000017) episodes (Warne et al, 2012).…”
Section: Resultsmentioning
confidence: 93%
“…Answering these questions will take more research on a wide array of gifted populations. I believe that the field of gifted education is ready for more psychometric research because gifted education is undergoing a revolution in methodology and statistics, as demonstrated by several recent works (Matthews et al, 2008;McCoach, Rambo, & Welsh., 2013;Shore, 2006;Thompson & Subotnik, 2010;VanTassel-Baska, 2006;Warne et al, 2012). Above-level testing is an ideal battlefront for this revolution because the practice is so widely accepted, yet poorly understood.…”
Section: Resultsmentioning
confidence: 99%