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dc.contributor.advisorMatis, James H.
dc.contributor.advisorStenning, Walter F.
dc.creatorRich, Franklin Delano
dc.descriptionIncludes bibliographical references (leaves 98-103)en
dc.description.abstractThe development of quantitive research intergation for a large number of studies on a given topic leading to Glass's technique of meta-analysis using calculated effect size is examined. Nonparametric statistical data analysis methods are examined and illustrated, including Tukey's box-and-whiskers plot, quantile functions, and Parzen's quantile-box plots and goodness-of-fit techniques. A quantile-box plot method of analyzing effect size data from meta-analysis is described for use in determining the nature of the distribution form of effect size data before full-scale meta-analysis. In particular, the quantile-box plot method is applied to real meta-analysis data sets from pretest sensitization studies. The quantile-box plot analysis illustrates near-normality of these effect size data, lending credibility to the original assumption of normality of the effect size data for pretest sensitization effects. How a 21-number summary of effect size data can quickly provide information on their distribution characteristics is examined. It is recommended that all effect size data sets be summarized using the 21-numbers and that these and a quantile-box plot be routinely published in any meta-analysis study for which original effect size cannot be included.en
dc.format.extentxii, 107 leaves : illustrationsen
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectEducational Curriculum and Instructionen
dc.subject.classification1981 Dissertation R498
dc.subject.lcshEducational statisticsen
dc.subject.lcshNonparametric statisticsen
dc.subject.lcshSocial sciences--Statistical methodsen
dc.subject.lcshEducational Curriculum and Instructionen
dc.titleMeta-analysis data : application of quantile function techniquesen
dc.typeThesisen A&M Universityen of Philosophyen
dc.contributor.committeeMemberJohnson, Glenn R.
dc.contributor.committeeMemberRinger, Larry J.
dc.format.digitalOriginreformatted digitalen
dc.publisher.digitalTexas A&M University. Libraries

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