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Statistical Regression Modeling with R: Longitudinal and Multi-Level Modeling (2021)Paperback - 2021, 10 April 2022

Statistical Regression Modeling with R: Longitudinal and Multi-Level Modeling (2021)
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Part of Series
Emerging Topics in Statistics and Biostatistics
Print Length
228 pages
Language
English
Publisher
Springer
Date Published
10 Apr 2022
ISBN-10
3030675858
ISBN-13
9783030675851

Description

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.

Product Details

Authors:
ChenJenny K Chen
Book Edition:
2021
Book Format:
Paperback
Country of Origin:
NL
Date Published:
10 April 2022
Dimensions:
23.39 x 15.6 x 1.32 cm
ISBN-10:
3030675858
ISBN-13:
9783030675851
Language:
English
Location:
Cham
Pages:
228
Publisher:
Weight:
353.8 gm

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