Statistical Regression Modeling with R : Longitudinal and Multi-level Modeling
Language: English
Published by Springer, 2022
Series: Book 6 of 7 - Emerging Topics in Statistics and Biostatistics
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - 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 Modelingpromotes 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.…
Seller Inventory # 9783030675851
- Title
- Statistical Regression Modeling with R : Longitudinal and Multi-level Modeling
- Author
- Jenny K. Chen
- Publisher
- Springer
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030675858
- ISBN 13
- 9783030675851
- Item weight
- 382 grams
- Dimensions
- 235x155x14 mm
- Series
- Book 6 of 7: Emerging Topics in Statistics and Biostatistics
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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