Conducting Meta-Analysis Using SAS, Arthur, Jr.

Автор: Tom M. Palmer and Jonathan A. C. Sterne (editors)
Название: Meta-Analysis in Stata
ISBN: 1597181471 ISBN-13(EAN): 9781597181471
Издательство: Taylor&Francis
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Цена: 77570.00 T
Наличие на складе: Невозможна поставка.
Описание: Meta-analysis allows researchers to combine the results of several studies into a unified analysis that provides an overall estimate of the effect of interest. This collection of articles from the Stata Journal and Stata Technical Bulletin will be indispensable to researchers who wish to conduct meta-analyses using Stata and learn about the full range of user-written Stata meta-analysis commands. With these articles and the associated Stata software, you gain access to the statistical methods behind the rapid increase in the number of meta-analyses reported in the social and medical literature. Collectively, the articles provide a detailed description of a range of meta-analytic methods. They show how to conduct and interpret meta-analyses; how to produce highly flexible graphical displays; how to use meta-regression; how to examine bias; how to conduct individual participant data meta-analysis; and how to conduct multivariate meta-analysis. This edition also contains three articles on network metaanalysis, a major recent development in meta-analysis methodology.

Автор: Koricheva Julia
Название: Handbook of Meta-Analysis in Ecology and Evolution
ISBN: 0691137293 ISBN-13(EAN): 9780691137292
Издательство: Wiley
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Цена: 82370.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets "--

Автор: Kulinskaya, E Morgenthaler, Stephan Staudte, Rober
Название: Meta analysis
ISBN: 0470028645 ISBN-13(EAN): 9780470028643
Издательство: Wiley
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Цена: 67530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence. The book is comprised of two parts - The Handbook, and The Theory.

Автор: Lewis
Название: Complex Survey Data Analysis with SAS
ISBN: 1498776779 ISBN-13(EAN): 9781498776776
Издательство: Taylor&Francis
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Цена: 91860.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Complex Survey Data Analysis with SAS (R) is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors.