Bayesian Meta-Analysis: A Practical
Bayesian Meta-Analysis: A Practical Introduction by Robert Grant, Gian Luca Di Tanna
- Bayesian Meta-Analysis: A Practical Introduction
- Robert Grant, Gian Luca Di Tanna
- Page: 328
- Format: pdf, ePub, mobi, fb2
- ISBN: 9781032451893
- Publisher: CRC Press
Books to download to ipad free Bayesian Meta-Analysis: A Practical Introduction 9781032451893 (English literature) by Robert Grant, Gian Luca Di Tanna
"…this book is extremely timely…not just a technical exposition, but provides practical guidance about using different software platforms, as well as valuable advice about extracting summary statistics, eliciting prior information, communicating results, visualisation, and many other issues…reflects years of thoughtful experience, and should be of huge value to anyone faced with pooling studies into a coherent whole." ~From the Foreword by Professor Sir David Spiegelhalter Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages. Key Features Introductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchers Examples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASP Practical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findings Discussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examples Accompanying online blog and forum, with all code and data from the book, plus more translations to different software This book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications.
What is the best book to learn Meta-Analysis that I can recommend .
It depends, if you want a theoretical basic book , I think “Introduction to Meta-Analysis" by Borenstein and others would be of great value.
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Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both.
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This online course will introduce the Bayesian approach to meta-analysis. Attendees will learn practical ways in which they can combine multiple sources of .
[PDF] The BUGS Book: A Practical Introduction to Bayesian Analysis
Miller, Jr. The BUGS Book: A Practical Introduction to. Bayesian Analysis. D. Lunn, C. Jackson, N. Best, A.
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[Q] Best textbook to teach Bayes? : r/statistics - Reddit
Statistical Rethinking, Doing Bayesian Data Analysis and Bayesian Data Analysis are all great books, but boy do they differ in terms of depth and difficulty.
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guide includes practical exercises and examples to facilitate hands-on learning . 13.3 Bayesian Meta-Analysis in R .
Introduction to Meta-Analysis Book
This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies.
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$74.99 · Introductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchers · Examples of basic meta-analyses .