Statistical Regression Modeling with R: Longitudinal and Multi-Level Modeling
暫譯: 使用 R 進行統計回歸建模：縱向與多層次建模

Chen, Ding-Geng (Din), Chen, Jenny K.

Statistical Regression Modeling with R: Longitudinal and Multi-Level Modeling
  • 出版商: Springer
  • 出版日期: 2021-04-09
  • 售價: $5,220
  • 貴賓價: 9.5 折 $4,959
  • 語言: 英文
  • 頁數: 228
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3030675823
  • ISBN-13: 9783030675820
  • 相關分類: R 語言

    • 海外代購書籍(需單獨結帳)

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商品描述

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.

商品描述(中文翻譯)

本書提供了最常用的迴歸方法的簡明參考。內容從適用於常態分佈數據的線性和非線性迴歸開始，接著介紹適用於二項分佈數據的邏輯迴歸，以及適用於計數數據的泊松迴歸和負二項迴歸。然後，書中進一步探討適用於縱向和多層次數據結構的迴歸模型。本書旨在指導從傳統迴歸建模過渡到更高級的迴歸建模，並促進統計學和數據科學的快速發展。透過提供數據和計算程式以促進讀者的學習體驗，《Statistical Regression Modeling》推廣了 R 在線性、非線性、縱向和多層次迴歸中的應用。所有包含的數據集以及與多層次迴歸相關的 R 程式，均在附錄 A 中詳細說明。本書對於應用迴歸的研究生課程，以及數據科學、統計分析、公共衛生及相關領域的從業者和研究人員都將具有重要價值。

作者簡介

Dr. Ding-Geng Chen is a fellow of the American Statistical Association and currently the Wallace H. Kuralt Distinguished Professor at the University of North Carolina at Chapel Hill. He was a professor in biostatistics at the University of Rochester and the Karl E. Peace Endowed Eminent Scholar Chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceutical organizations and government agencies with extensive expertise in Monte Carlo simulations, clinical trial biostatistics, and public health statistics. Dr. Chen has more than 200 professional publications, and he has coauthored/coedited 31 books on clinical trial methodology, meta-analysis, data sciences, Monte Carlo simulation-based statistical modeling, and public health applications. He has been invited nationally and internationally to give speeches on his research.

Ms. Jenny K. Chen graduated with a master's degree from the Department of Statistics and Data Science at Cornell University. She is currently working as a financial analyst at Morgan Stanley (Midtown New York Office) for their Wealth Management division. Previously, Jenny worked as a product manager for Google, where she led a team of data scientists to develop several prediction algorithms for the 2019 NCAA March Madness Basketball Tournament. She has published several research papers in statistical modeling and data analytics.

作者簡介(中文翻譯)

陳丁耕博士是美國統計學會的會士，目前擔任北卡羅來納大學教堂山分校的華萊士·H·庫拉特傑出教授。他曾在羅徹斯特大學擔任生物統計學教授，並在喬治亞南方大學擔任卡爾·E·皮斯捐贈的傑出學者椅。他同時也是生物製藥組織和政府機構的高級統計顧問，擁有豐富的蒙地卡羅模擬、臨床試驗生物統計學和公共衛生統計的專業知識。陳博士擁有超過200篇專業出版物，並共同撰寫/編輯了31本有關臨床試驗方法學、統合分析、數據科學、基於蒙地卡羅模擬的統計建模和公共衛生應用的書籍。他曾在國內外受邀發表有關其研究的演講。

陳建妤女士畢業於康奈爾大學統計與數據科學系，獲得碩士學位。她目前在摩根士丹利（紐約中城辦公室）擔任財務分析師，負責其財富管理部門。之前，建妤曾在谷歌擔任產品經理，領導一個數據科學家團隊為2019年NCAA三月瘋狂籃球賽開發幾個預測算法。她在統計建模和數據分析方面發表了幾篇研究論文。

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