Normal view MARC view ISBD view

Applied meta-analysis with R

By: Chen, Ding-Geng (Din).
Contributor(s): Peace, Karl E.
Series: Chapman &​ Hall/​CRC biostatistics series. Publisher: Boca Raton CRC Press 2013Description: xxiv, 321 p.ISBN: 9781466505995.Subject(s): Meta-analysis | R (Computer program language) | Biostatistics | Probability and Statistics -​ GeneralDDC classification: 570.15195 Summary: In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. 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 packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. 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) in public health, medical research, governmental agencies, and the pharmaceutical industry. (https://www.crcpress.com/Applied-Meta-Analysis-with-R/Chen-Peace/9781466505995)
List(s) this item appears in: VR_Healthcare Analytics | Laha
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Item location Collection Call number Status Date due Barcode
Books Vikram Sarabhai Library
Slot 1700 (2 Floor, East Wing) Non-fiction 570.15195 C4A7 (Browse shelf) Available 190416

Table of contents:

1. Introduction to R
2. Research Protocol for Meta-Analyses
3. Fixed-Effects and Random-Effects in Meta-Analysis
4. Meta-Analysis with Binary Data
5. Meta-Analysis for Continuous Data
6. Heterogeneity in Meta-Analysis
7. Meta-Regression
8. Individual-Patient Level Data Analysis versus Meta-Analysis
9. Meta-Analysis for Rare Events
10. Other R Packages for Meta-Analysis

In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R.
Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. 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 packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data.
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) in public health, medical research, governmental agencies, and the pharmaceutical industry.

(https://www.crcpress.com/Applied-Meta-Analysis-with-R/Chen-Peace/9781466505995)

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha