By Terri D. Pigott (auth.)

ISBN-10: 1461422779

ISBN-13: 9781461422778

The topic of the ebook is complicated statistical analyses for quantitative examine synthesis (meta-analysis), and chosen sensible matters on the subject of examine synthesis that aren't lined intimately within the many current introductory books on examine synthesis (or meta-analysis). advanced statistical concerns are coming up extra often because the basic learn that's summarized in quantitative syntheses itself turns into extra complicated, and as researchers who're undertaking meta-analyses turn into extra formidable within the questions they want to deal with. additionally as researchers have received extra event in engaging in study syntheses, numerous key concerns have continued and now seem primary to the firm of summarizing research.

Specifically the e-book describes multivariate analyses for a number of indices known in meta-analysis (e.g., correlations, impression sizes, proportions and/or odds ratios), will define easy methods to do energy research for meta-analysis (again for every of the various varieties of research consequence indices), and examines matters round learn caliber and study layout and their roles in synthesis. for every of the statistical issues we'll study different attainable statistical types (i.e., mounted, random, and combined types) that may be followed by means of a researcher. In facing the problems of analysis caliber and study layout it covers a couple of particular issues which are of large drawback to investigate synthesists. in lots of fields a present factor is easy methods to make experience of effects whilst reports utilizing a number of various designs seem in a learn literature (e.g., Morris & Deshon, 1997, 2002). In schooling and different social sciences a serious point of this factor is how one may possibly contain qualitative (e.g., case learn) study inside a synthesis. In drugs, similar concerns hindrance even if and the way to summarize observational stories, and whether or not they will be mixed with randomized managed trials (or no matter if they need to be mixed at all).

For each one subject, integrated is a labored instance (e.g., for the statistical analyses) and/or a close description of a printed learn synthesis that offers with the sensible (non-statistical) matters lined.

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I take an alternative view of the value of a power analysis in research synthesis. As emphasized in Chap. 3, knowledge of an area is critical to the planning of a synthesis, especially with regard to planning the moderator analyses carefully so as to avoid Type I errors. The same could be argued for the importance of a power analysis as preliminary to a systematic review. D. 1007/978-1-4614-2278-5_4, # Springer Science+Business Media, LLC 2012 35 36 4 Power Analysis for the Mean Effect Size considered substantively important and of the statistical methods (such as moderator analyses) that will be used.

1 involves the computation of the variance component using restricted maximum likelihood. 3. The first program enters the data used in this example. The variables are the study name, the correlation, Fisher’s z corresponding to the correlation, the variance of Fisher’s z, a code that takes the value 1 for studies using state tests for achievement, and 2 for standardized tests, and the study weight. The second program provides the code to compute the variance component using restricted maximum likelihood.

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Advances in Meta-Analysis by Terri D. Pigott (auth.)

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