Applied Meta-Analysis with R and Stata
暫譯: 使用 R 和 Stata 的應用型元分析

Chen, Ding-Geng (Din), Peace, Karl E.

Applied Meta-Analysis with R and Stata
  • 出版商: CRC
  • 出版日期: 2022-09-26
  • 售價: $2,400
  • 貴賓價: 9.5 折 $2,280
  • 語言: 英文
  • 頁數: 424
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0367709341
  • ISBN-13: 9780367709341
  • 相關分類: R 語言
  • 其他版本: Applied Meta-Analysis with R and Stata

    • 立即出貨 (庫存=1)

商品描述

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.

商品描述(中文翻譯)

第一版的評價：

作者努力將理論減至最低，使其成為一本適合生物學家、醫生等缺乏高級數學背景的自學教材。與許多其他教科書不同，R並不是用無意義的玩具範例來介紹；相反，讀者將被引導直接了解一些與元分析直接相關的分析、圖形和模擬……這是一本對於希望熟悉元分析基本概念並開始實作的從業者來說非常有用的實用指南，而無需深入研究定理和證明。

-應用統計學期刊

使用R和Stata的統計元分析，第二版提供了對統計元分析（MA）的全面介紹，並使用R/Stata進行逐步實作。作者逐步使用適當的R/Stata函數開展分析，使讀者能夠理解元分析方法及其在R/Stata中的實作，從而能夠使用這兩個流行的軟體包來分析自己的元數據。每一章都提供了來自文獻的真實研究範例。在介紹數據和理解應用所需的背景後，介紹了各種分析元數據的方法。然後，作者使用適當的R/Stata套件和函數開發分析代碼。

 

第二版的新內容：

 


  • 新增Stata程式，與R程式一起用於元分析

  • 更新所有使用R/Stata程式的統計元分析

  • 涵蓋固定效應和隨機效應的MA、元回歸、稀有事件的MA，以及MA-IPD與MA-SS的比較

  • 新增五章關於多變量MA、出版偏差、MA中的缺失數據、評估診斷準確性的MA，以及網絡MA

 

本書適合作為研究生層級的元數據分析課程教材，對於公共衛生、醫學研究、政府機構和製藥行業的從業者和生物統計學家（即使是對使用R或Stata幾乎沒有經驗的人）來說，也是一本寶貴的參考書。

作者簡介

Ding-Geng (Din) Chen is a fellow of American Statistical Association and currently the Wallace H. Kuralt Distinguished Professor at the University of North Carolina-Chapel Hill, USA. Formerly, he was a Professor of Biostatistics at the University of Rochester, New York, USA, the Karl E. Peace Endowed Eminent Scholar Chair and professor in Biostatistics in the Jiann-Ping Hsu College of Public Health at Georgia Southern University, USA, and a professor of statistics at South Dakota Stata University, USA. Dr. Chen's research interests include clinical trial biostatistical methodological development in Bayesian models, survival analysis, multi-level modelling and longitudinal data analysis, and statistical meta-analysis. He has published more than 200 refereed papers and co-authored/co-edited 30 book in statistics.

Karl E. Peace is the Georgia Cancer Coalition Distinguished Cancer Scholar, Founding Director of the Center for Biostatistics, Professor of Biostatistics, and Senior Research Scientist in the Jiann-Ping Hsu College of Public Health at Georgia Southern University (GSU). Dr. Peace has made pivotal contributions in the development and approval of drugs to treat numerous diseases and disorders. A fellow of the ASA, he has been a recipient of many honors, including the Drug Information Association Outstanding Service Award, the American Public Health Association Statistics Section Award, The First recipient of the President's Medal for outstanding contributions to GSU, and recognition by the Georgia and US Houses of Representatives, and the Virginia House of Delegates.

作者簡介(中文翻譯)

陳丁耕（Din Chen）是美國統計學會的會士，目前擔任美國北卡羅來納州教堂山的華萊士·H·庫拉特傑出教授。之前，他曾是美國紐約羅徹斯特大學的生物統計學教授，並在美國喬治亞南方大學的簡平徐公共衛生學院擔任卡爾·E·皮斯捐贈的傑出學者主席及生物統計學教授，還曾是美國南達科他州立大學的統計學教授。陳博士的研究興趣包括貝葉斯模型的臨床試驗生物統計方法開發、生存分析、多層次建模和縱向數據分析，以及統計元分析。他已發表超過200篇經過審核的論文，並共同撰寫或編輯了30本統計學書籍。

卡爾·E·皮斯（Karl E. Peace）是喬治亞癌症聯盟的傑出癌症學者，生物統計學中心的創始主任，生物統計學教授，以及喬治亞南方大學（GSU）簡平徐公共衛生學院的高級研究科學家。皮斯博士在開發和批准治療多種疾病和障礙的藥物方面做出了關鍵貢獻。作為美國統計學會的會士，他獲得了許多榮譽，包括藥物信息協會的傑出服務獎、美國公共衛生協會統計部門獎、GSU傑出貢獻的總統獎章的首位獲得者，以及喬治亞州和美國眾議院及維吉尼亞州代表大會的表彰。

類似商品