Confidence Intervals for Discrete Data in Clinical Research
暫譯: 臨床研究中離散數據的信賴區間
Pradhan, Vivek, Gangopadhyay, Ashis, Menon, Sandeep M.
- 出版商: CRC
- 出版日期: 2021-11-15
- 售價: $4,910
- 貴賓價: 9.5 折 $4,665
- 語言: 英文
- 頁數: 226
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1138048984
- ISBN-13: 9781138048980
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相關分類:
機率統計學 Probability-and-statistics、Data Science
海外代購書籍(需單獨結帳)
商品描述
Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas in clinical research. The array of methodologies available in the literature to address the inferential questions for binomial and multinomial data can be a double-edged sword. On the one hand, these methods open a rich avenue of exploration of data; on the other, the wide-ranging and competing methodologies potentially lead to conflicting inferences, adding to researchers' confusion and frustration and also leading to reporting bias. This book addresses the problems that many practitioners experience in choosing and implementing fit for purpose data analysis methods to answer critical inferential questions for binomial and count data.
The book is an outgrowth of the authors' collective experience in biomedical research and provides an excellent overview of inferential questions of interest for binomial proportions and rates based on count data, and reviews various solutions to these problems available in the literature. Each chapter discusses the strengths and weaknesses of the methods and suggests practical recommendations. The book's primary focus is on applications in clinical research, and the goal is to provide direct benefit to the users involved in the biomedical field.
商品描述(中文翻譯)
《臨床研究中離散數據的信賴區間》旨在為生物醫學研究人員提供一個工具箱。離散數據的分析是臨床研究中最常用但又令人困惑的領域之一。文獻中可用於解決二項和多項數據推論問題的方法多種多樣，這可能是一把雙刃劍。一方面，這些方法為數據探索開啟了豐富的途徑；另一方面，廣泛且競爭的方法可能導致相互矛盾的推論，增加研究人員的困惑和挫折感，並導致報告偏差。本書針對許多實務工作者在選擇和實施適合目的的數據分析方法以回答二項和計數數據的關鍵推論問題時所遇到的問題進行探討。
本書是作者在生物醫學研究中集體經驗的延伸，提供了基於計數數據的二項比例和比率的推論問題的優秀概述，並回顧了文獻中可用的各種解決方案。每一章節討論了這些方法的優缺點並提出實用建議。本書的主要重點是臨床研究中的應用，目標是為參與生物醫學領域的用戶提供直接的利益。
作者簡介
Vivek Pradhan has been working in the industry for more than twenty years. Currently he is a senior director in statistics in Early Clinical Development of Pfizer where he is responsible for managing all the statistical aspects of drug development from pre-clinical to Phase IIB trials. He has been publishing methodological papers on discrete data, and a regular invited speaker in several industry conferences and forums.
Ashis K Gangopadhyay is an Associate Professor of Statistics in the Department of Mathematics and Statistics at Boston University. His research areas include predictive modeling in clinical research, nonparametric and semiparametric methods, and analysis of financial data. He has authored numerous extensively cited research papers and mentored many Ph.D. students.
Sandeep Menon is Senior Vice President and the Head of Early Clinical Development at Pfizer Inc. and holds Adjunct faculty positions at Boston University School of Public Health, Tufts University School of Medicine, and the Indian Institute of Management. At Pfizer, he is in the Worldwide Research, Development and Medical Leadership Team and leads a multi-functional global team. Before joining the industry, he practiced medicine in Mumbai and was Resident Medical Officer. Sandeep is an elected fellow of the American Statistical Association (ASA), awarded the Young Scientist Award by the International Indian Statistical Association, the Statistical Excellence Award in Pharmaceutical Industry by Royal Statistical Society, UK and recently awarded the Distinguished Alumni Award by the Department of Biostatistics at Boston University School of Public Health. He received his medical degree from Karnataka University, India, and later completed his Masters in Epidemiology and Biostatistics and Ph.D. in Biostatistics at Boston University and research Assistantship at Harvard Clinical Research Institute. He has published more than 50 scientific original publications and book chapters and co-authored /co-edited six books.
Cynthia Basu has been involved in research in clinical trials and Bayesian methods. She is currently an associate director of statistics in Early Clinical Development at Pfizer where she works on early phase trials in Oncology. Her research interests include topics in clinical trial designs, Bayesian methods, adaptive trials, and historical borrowing.
Tathagata Banerjee has been engaged in teaching and research in statistics for more than three decades. Currently, he is a professor at the Indian Institute of Management Ahmedabad, India. His research interest is primarily focused on developing statistical methodologies for drawing inference from different kinds of data. His research is published regularly in peer reviewed journals, and he has given lectures and taught in various universities across the world.
作者簡介(中文翻譯)
維維克·普拉丹在業界工作超過二十年。目前，他是輝瑞（Pfizer）早期臨床開發部門的高級總監，負責管理從臨床前到IIB期試驗的所有統計方面。他在離散數據的研究方法上發表了多篇論文，並且是多個行業會議和論壇的定期受邀演講者。
阿希斯·K·甘戈帕迪亞是波士頓大學數學與統計系的副教授。他的研究領域包括臨床研究中的預測建模、非參數和半參數方法，以及金融數據分析。他撰寫了多篇被廣泛引用的研究論文，並指導了許多博士生。
桑迪普·梅農是輝瑞公司早期臨床開發部的高級副總裁，並在波士頓大學公共衛生學院、塔夫茨大學醫學院和印度管理學院擔任兼任教職。在輝瑞，他是全球研究、開發和醫療領導團隊的一員，並領導一個多功能的全球團隊。在進入業界之前，他在孟買執業醫療，並擔任住院醫師。桑迪普是美國統計協會（ASA）的當選會員，曾獲得國際印度統計協會的青年科學家獎、英國皇家統計學會的製藥行業統計卓越獎，並最近獲得波士頓大學公共衛生學院生物統計系的傑出校友獎。他在印度卡納塔克大學獲得醫學學位，後來在波士頓大學完成流行病學和生物統計學碩士學位及生物統計學博士學位，並在哈佛臨床研究所擔任研究助理。他已發表超過50篇科學原創出版物和書籍章節，並共同撰寫/編輯六本書籍。
辛西婭·巴蘇參與了臨床試驗和貝葉斯方法的研究。她目前是輝瑞早期臨床開發部的統計副總監，專注於腫瘤學的早期階段試驗。她的研究興趣包括臨床試驗設計、貝葉斯方法、自適應試驗和歷史借用等主題。
塔塔哈加塔·班納吉從事統計教學和研究已超過三十年。目前，他是印度艾哈邁達巴德管理學院的教授。他的研究興趣主要集中在為不同類型數據開發統計方法論。他的研究定期發表在同行評審的期刊上，並在世界各地的多所大學進行講座和教學。
