Beyond Multiple Linear Regression: Applied Generalized Linear Models And Multilevel Models in R
暫譯: 超越多重線性回歸：在 R 中應用廣義線性模型與多層次模型
Roback, Paul, Legler, Julie
- 出版商: CRC
- 出版日期: 2020-12-29
- 售價: $4,110
- 貴賓價: 9.5 折 $3,905
- 語言: 英文
- 頁數: 436
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1439885389
- ISBN-13: 9781439885383
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相關主題
商品描述
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling.
A solutions manual for all exercises is available to qualified instructors at the book's website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors' GitHub repo (https: //github.com/proback/BeyondMLR)
商品描述(中文翻譯)
《超越多重線性回歸：在 R 中應用廣義線性模型和多層次模型》旨在幫助已成功完成多重線性回歸課程的本科生，發展一套擴展的建模工具包，包括非正態反應和相關結構。儘管沒有數學先修課程的要求，作者仍以直觀和應用的方式介紹相當複雜的主題，如似然理論（likelihood theory）、零膨脹泊松（zero-inflated Poisson）和參數自助法（parametric bootstrapping）。案例研究和練習使用真實數據和真實研究問題，因此，教科書中的大部分數據來自作者及其學生的合作研究或學生專案。每一章都包含各種概念性練習、引導性練習和開放式練習，使用真實數據。完成這些材料後，學生將發展出擴展的工具包，並對數據和統計建模的更廣泛世界有更深的理解。
所有練習的解答手冊可在本書網站 www.routledge.com 上提供給合格的教師，所有案例研究和練習的數據集和 Rmd 文件可在作者的 GitHub 倉庫（https://github.com/proback/BeyondMLR）中獲得。
作者簡介
Authors
Paul Roback is the Kenneth O. Bjork Distinguished Professor of Statistics and Data Science and Julie Legler is Professor Emeritus of Statistics at St. Olaf College in Northfield, MN. Both are Fellows of the American Statistical Association and are founders of the Center for Interdisciplinary Research at St. Olaf. Dr. Roback is the past Chair of the ASA Section on Statistics and Data Science Education, conducts applied research using multilevel modeling, text analysis, and Bayesian methods, and has been a statistical consultant in the pharmaceutical, health care, and food processing industries. Dr. Legler is past Chair of the ASA/MAA Joint Committee on Undergraduate Statistics, is a co-author of Stat2: Modelling with Regression and ANOVA, and was a biostatistician at the National Cancer Institute.
作者簡介(中文翻譯)
作者
保羅·羅巴克是明尼蘇達州北菲爾德聖奧拉夫學院的肯尼斯·O·比約克統計與數據科學傑出教授，朱莉·萊格勒是該校的統計學名譽教授。兩人均為美國統計學會的會士，並且是聖奧拉夫學院跨學科研究中心的創始人。羅巴克博士曾擔任美國統計學會統計與數據科學教育分會的主席，進行應用研究，使用多層次建模、文本分析和貝葉斯方法，並在製藥、醫療保健和食品加工行業擔任統計顧問。萊格勒博士曾擔任美國統計學會/數學協會本科統計聯合委員會的主席，是Stat2: Modelling with Regression and ANOVA的共同作者，並曾在國家癌症研究所擔任生物統計學家。
