Statistical meta-analysis with applications
"Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on...
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Main Authors: | |
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Group Author: | ; |
Published: |
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Literature type: | Electronic eBook |
Language: | English |
Series: |
Wiley series in probability and statistics
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Subjects: | |
Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/9780470386347 |
Summary: |
"Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of up-to-date information, this book successfully introduces the essential statistical practices for making thorough and accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmental studies."--Jacket. |
Carrier Form: | 1 online resource (xv, 247 pages) : illustrations. |
Bibliography: | Includes bibliographical references (pages 233-244) and index. |
ISBN: |
9780470386330 (electronic bk.) 0470386339 (electronic bk.) 9780470386347 0470386347 |
Index Number: | QA277 |
CLC: | O212.1 |
Contents: | Introduction -- Various measures of effect size -- Combining independent tests -- Methods of combining effect sizes -- Inference about a common mean of several univariate normal populations -- Tests of homogeneity in meta-analysis -- One-way random effects model -- Combining controlled trials with normal outcomes -- Combining controlled trials with discrete outcomes -- Meta-regression -- Multivariate meta-analysis -- Bayesian meta-analysis -- Publication bias -- 14. Recovery of inter-block information -- Combination of polls -- Vote counting procedures -- Computational aspects data sets. |