Meta Analysis
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A01=Elena Kulinskaya
A01=Robert G. Staudte
A01=Stephan Morgenthaler
account
accurate estimation
allows
analysis
Author_Elena Kulinskaya
Author_Robert G. Staudte
Author_Stephan Morgenthaler
between study
calibration
Category=PBT
common
conditions
differences
different
effects
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
interest
low power
meta
number
overcome
results
sample
scale
sizes
studies
suffer
transformed
Product details
- ISBN 9780470028643
- Weight: 431g
- Dimensions: 154 x 229mm
- Publication Date: 29 Feb 2008
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Paperback
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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.
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.
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.
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.
