Elena Kulinskaya, Stephan Morgenthaler, Robert G. Staudte

Meta Analysis (eBook, PDF)

A Guide to Calibrating and Combining Statistical Evidence

• Format: PDF

Produktbeschreibung

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. The Handbook is a guide for combining and interpreting experimental evidence to solve standard statistical problems. This section allows someone with a rudimentary knowledge in general statistics to apply the methods. The Theory provides the motivation, theory and results of simulation experiments to justify the methodology. This is a coherent introduction to the statistical concepts required to understand the authors' thesis that evidence in a test statistic can often be calibrated when transformed to the right scale.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 282
• Erscheinungstermin: 2. August 2008
• Englisch
• ISBN-13: 9780470985526
• Artikelnr.: 37301405

Autorenporträt

Dr. E. Kulinskaya - Director, Statistical Advisory Service, Imperial College, London. Professor S. Morgenthaler - Chair of Applied Statistics, Ecole Polytechnique Fédérale de Lausanne, Switzerland. Professor Morgenthaler was Assistant Professor at Yale University prior to moving to EPFL and has chaired various ISI committees. Professor R. G. Staudte - Department of Statistical Science, La Trobe University, Melbourne. During his career at La Trobe he has served as Head of the Department of Statistical Science for five years and Head of the School of Mathematical and Statistical Sciences for two years. He was an Associate Editor for the Journal of Statistical Planning & Inference for 4 years, and is a member of the American Statistical Association, the Sigma Xi Scientific Research Society and the Statistical Society of Australia.

Inhaltsangabe

Preface. Part I The Methods. 1 What can the reader expect from this book? 2
Independent measurements with known precision. 3 Independent measurements
with unknown precision. 4 Comparing treatment to control. 5 Comparing K
treatments. 6 Evaluating risks. 7 Comparing risks. 8 Evaluating Poisson
rates. 9 Comparing Poisson rates. 10 Goodness-of-fit testing. 11 Evidence
for heterogeneity of effects and transformed effects. 12 Combining
evidence: fixed standardized effects model. 13 Combining evidence: random
standardized effects mode. 14 Meta-regression. 15 Accounting for
publication bias. Part II The Theory. 16 Calibrating evidence in a test. 17
The basics of variance stabilizing transformations. 18 One-sample binomial
tests. 19 Two-sample binomial tests. 20 Defining evidence in t-statistics.
21 Two-sample comparisons. 22 Evidence in the chi-squared statistic. 23
Evidence in F-tests. 24 Evidence in Cochran's Q for heterogeneity of
effects. 25 Combining evidence from K studies. 26 Correcting for
publication bias. 27 Large-sample properties of variance stabilizing
transformations. References. Index.