Statistical Meta-Analysis with Applications
Published on 20. September 2011
248 pages
978-1-118-21096-3 (ISBN)
Description
An accessible introduction to performing meta-analysis acrossvarious areas of research
The practice of meta-analysis allows researchers to obtainfindings from various studies and compile them to verify and formone overall conclusion. Statistical Meta-Analysis with Applicationspresents the necessary statistical methodologies that allow readersto tackle the four main stages of meta-analysis: problemformulation, data collection, data evaluation, and data analysisand interpretation. Combining the authors' expertise on the topicwith a wealth of up-to-date information, this book successfullyintroduces the essential statistical practices for making thoroughand accurate discoveries across a wide array of diverse fields,such as business, public health, biostatistics, and environmentalstudies.
Two main types of statistical analysis serve as the foundationof the methods and techniques: combining tests of effect size andcombining estimates of effect size. Additional topics coveredinclude:
* Meta-analysis regression procedures
* Multiple-endpoint and multiple-treatment studies
* The Bayesian approach to meta-analysis
* Publication bias
* Vote counting procedures
* Methods for combining individual tests and combining individualestimates
* Using meta-analysis to analyze binary and ordinal categoricaldata
Numerous worked-out examples in each chapter provide the readerwith a step-by-step understanding of the presented methods. Allexercises can be computed using the R and SAS software packages,which are both available via the book's related Web site. Extensivereferences are also included, outlining additional sources forfurther study.
Requiring only a working knowledge of statistics, StatisticalMeta-Analysis with Applications is a valuable supplement forcourses in biostatistics, business, public health, and socialresearch at the upper-undergraduate and graduate levels. It is alsoan excellent reference for applied statisticians working inindustry, academia, and government.
Reviews / Votes
"The strength of this book is certainly the detailed development and presentation of inference for normal fixed and random effects models as applied in meta-analysis and similar studies, such as inter-laboratory studies. A particularly well done part of the book centers on homogeneity testing and on confidence interval estimation of the so-called heterogeneity parameter in the standard random effects model." (Journal of Biopharmaceutical Statistics, January 2010) "The authors have written a good guide to a broad section of the methods available for statistical meta-analysis." (Mathematical Reviews, 2009) "[The authors], active researchers themselves, have done a commendable job in writing this introductory book noted for its clarity and style of presentation and coverage of some totally new topics." (Choice, April 2009)More details
Other editions
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Joachim Hartung | Guido Knapp | Bimal K. Sinha
Statistical Meta-Analysis with Applications
Software
08/2008
Wiley
€147.88
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Joachim Hartung | Guido Knapp | Bimal K. Sinha
Statistical Meta-Analysis with Applications
Book
08/2008
Wiley
€154.50
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Persons
JOACHIM HARTUNG, PhD, is Professor in the Department ofStatistics at the Dortmund University of Technology, Germany. Hehas published several books and two dozen journal articles in thefield of statistics.
GUIDO KNAPP, PhD, is Assistant Professor in theDepartment of Statistics at the Dortmund University of Technology,Germany. Dr. Knapp's areas of research interest include variancecomponent models, error components regression models,meta-analysis, and flexible design in clinical trials.
BIMAL K. SINHA, PhD, is Presidential Research Professorof Statistics in the Department of Mathematics and Statistics atthe University of Maryland at Baltimore County (UMBC). A Fellow ofboth the Institute of Mathematical Statistics and the AmericanStatistical Association, Dr. Sinha's research specializes in theareas of multivariate analysis, mixed linear models, decisiontheory, robustness, and environmental statistics.
Content
Preface.
1. Introduction.
2. Various Measures of Effect Size.
2.1 Effect Size based on Means.
2.2 Effect Size based on Proportions.
2.3 Effect Size based on - Coefficient and Odds Ratio.
2.4 Effect Size based on Correlation.
3. Combining Independent Tests.
3.1 Introduction.
3.2 Description of Combined Tests.
4. Methods of Combining Effect Sizes.
5. Inference about a Common Mean of Several Univariate NormalPopulations.
5.1 Results on Common Mean Estimation.
5.2 Asymptotic Comparison of Some Estimates of Common Mean for k= 2 Populations.
5.3 Confidence Intervals for the Common Mean.
5.4 Applications.
5.5 Appendix: Theory of Fisher's Method.
6. Tests of Homogeneity in Meta-Analysis.
6.1 Model and Test Statistics.
6.2 An Exact Test of Homogeneity.
6.3 Applications.
7. One-Way Random Effects Model.
7.1 Introduction.
7.2 Homogeneous Error Variances.
7.3 Heterogeneous Error Variances.
8. Combining Controlled Trials with Normal Outcomes.
8.1 Difference of Means.
8.2 Standardized Difference of Means.
8.3 Ratio of Means.
9. Combining Controlled Trials with DiscreteOutcomes.
9.1 Binary Data.
9.2 Ordinal Data.
10. Meta-Regression.
10.1 Model with One Covariate.
10.2 Model with More Than One Covariate.
10.3 Further Extensions and Applications.
11. Multivariate Meta-Analysis.
11.1 Combining Multiple Dependent Variables from a SingleStudy.
11.2 Modeling Multivariate Effect Sizes.
12. Bayesian Meta-Analysis.
12.1 A General Bayesian Model for Meta-Analysis underNormality.
12.2 Further Examples of Bayesian Analyses.
12.3 A Unified Bayesian Approach to Meta-Analysis.
12.4 Further Results on Bayesian Meta-Analysis.
13. Publication Bias.
14. Recovery of Inter-Block Information.
14.1 Notations and Test Statistics.
14.2 BIBD with Fixed Treatment Effects.
15. Combination of Polls.
15.1 Formulation of the Problem.
15.2 Meta-Analysis of Polls.
16. Vote Counting Procedures.
17. Computational Aspects.
17.1 Extracting Summary Statistics.
17.2 Combining Tests.
17.3 Generalized P-values.
17.4 Combining Effect Sizes.
18. Data Sets.
18.1 Validity Studies.
18.2 Effects of Teacher Expectance on Pupil IQ.
18.3 Dentifrice Data.
18.4 Effectiveness of Amlodipine on Work Capacity.
18.5 Effectiveness of Cisapride on the Treatment of NonulcerDyspepsia.
18.6 Secondhand Smoking.
18.7 Effectiveness of Misoprostol in Preventing GastrointestinalDamage.
18.8 Prevention of Tuberculosis.
References.
Index.
