Multilevel Modeling Using R - Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences (Paperback)
  • Multilevel Modeling Using R - Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences (Paperback)
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Multilevel Modeling Using R - Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences (Paperback)

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£52.99
Paperback 242 Pages / Published: 15/05/2019
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Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment.

After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data.

New in the Second Edition:

Features the use of lmer (instead of lme) and including the most up to date approaches for obtaining confidence intervals for the model parameters.

Discusses measures of R2 (the squared multiple correlation coefficient) and overall model fit.

Adds a chapter on nonparametric and robust approaches to estimating multilevel models, including rank based, heavy tailed distributions, and the multilevel lasso.

Includes a new chapter on multivariate multilevel models.

Presents new sections on micro-macro models and multilevel generalized additive models.

This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research.

About the Authors:

W. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at Ball State University.

Jocelyn E. Bolin is a Professor in the Department of Educational Psychology at Ball State University.

Ken Kelley is the Edward F. Sorin Society Professor of IT, Analytics and Operations and the Associate Dean for Faculty and Research for the Mendoza College of Business at the University of Notre Dame.

Publisher: Taylor & Francis Ltd
ISBN: 9781138480674
Number of pages: 242
Weight: 363 g
Dimensions: 234 x 156 mm
Edition: 2nd New edition


MEDIA REVIEWS
"This book is the second edition of a hugely popular title on multilevel modelling (MLM) using R software. Assuming a basic understanding of how a linear regression model works, if someone is looking for a complete reference on how to fit multilevel models with R, then look no further. Even for those not accustomed to the mathematical details of regression modelling, the provided overview with practical examples and R code should get one up to speed. This book is concise, to the point, and a hands-on, how-to reference on multilevel modelling. Through their clear writing style, the authors have provided answers to all of the essential questions a practitioner might have in fitting a multilevel model. In essence, the book presents straightforward explanations of basic MLM, multilevel generalized linear models, Bayesian multilevel modelling, multivariate multilevel modelling, and how to fit them using R."
- Enayet Raheem, ISCB News, July 2020

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