| Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence Contributor(s): Kulinskaya, Elena (Author), Morgenthaler, Stephan (Author), Staudte, Robert G. (Author) |
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ISBN: 0470028645 ISBN-13: 9780470028643 Publisher: Wiley-Interscience OUR PRICE: $94.00 Product Type: Paperback - Other Formats Published: April 2008 Annotation: "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. |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Medical | Research |
| Dewey: 610.727 |
| LCCN: 2007045548 |
| Series: Wiley Series in Probability and Statistics |
| Physical Information: 0.64" H x 6.05" W x 8.91" (0.93 lbs) 282 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
