Applied Meta-Analysis with R and Stata

preview-18
  • Applied Meta-Analysis with R and Stata Book Detail

  • Author : Ding-Geng (Din) Chen
  • Release Date : 2021-03-30
  • Publisher : CRC Press
  • Genre : Computers
  • Pages : 457
  • ISBN 13 : 0429592175
  • File Size : 95,95 MB

Applied Meta-Analysis with R and Stata by Ding-Geng (Din) Chen PDF Summary

Book Description: 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.

Disclaimer: www.yourbookbest.com does not own Applied Meta-Analysis with R and Stata books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Applied Meta-Analysis with R and Stata

Applied Meta-Analysis with R and Stata

File Size : 54,54 MB
Total View : 5568 Views
DOWNLOAD

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, physic

Applied Meta-Analysis with R

Applied Meta-Analysis with R

File Size : 27,27 MB
Total View : 5127 Views
DOWNLOAD

In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedi

Applied Meta-Analysis with R

Applied Meta-Analysis with R

File Size : 97,97 MB
Total View : 1270 Views
DOWNLOAD

In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedi

Doing Meta-Analysis with R

Doing Meta-Analysis with R

File Size : 27,27 MB
Total View : 8732 Views
DOWNLOAD

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis

Meta-Analysis with R

Meta-Analysis with R

File Size : 84,84 MB
Total View : 2489 Views
DOWNLOAD

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and st