Meta Analysis
A Guide to Calibrating and Combining Statistical Evidence
Elena (Statistical Advisory Service) Kulinskaya, Stephan (Swiss Federal Institute of Technology) Morgenthaler, Robert G. (La Trobe University Australia) Staudte
Pocket
Engelsk
Wiley Series in Probability and Statistics
- Forfattere: Elena (Statistical Advisory Service) Kulinskaya , Stephan (Swiss Federal Institute of Technology) Morgenthaler , Robert G. (La Trobe University Australia) Staudte
- Format: Pocket
- Antall sider: 282
- Språk: Engelsk
- Forlag/Utgiver: SD Books
- Serienavn: Wiley Series in Probability and Statistics
- EAN: 9780470028643
- Utgivelsesår: 2008
- Bidragsyter: Kulinskaya, Elena (Statistical Advisory Service); Morgenthaler, Stephan (Swiss Federal Institute of Technology); Staudte, Robert G. (La Trobe University, Australia)
829,-
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.
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