Applied Meta-Analysis with R and Stata

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Synopsis

Review of the First Edition:
The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis… A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs.
—Journal of Applied Statistics
Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions.

What’s New in the Second Edition:


Adds Stata programs along with the R programs for meta-analysis


Updates all the statistical meta-analyses with R/Stata programs


Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS


Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA


Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.

Book details

Edition:
2
Series:
Chapman & Hall/CRC Biostatistics Series
Author:
Ding-Geng (Din) Chen, Karl E. Peace
ISBN:
9780429592171
Related ISBNs:
9780429061240, 9780367183837, 9780367709341
Publisher:
CRC Press
Pages:
424
Reading age:
Not specified
Includes images:
No
Date of addition:
2021-03-31
Usage restrictions:
Copyright
Copyright date:
2021
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Medicine, Nonfiction