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

Name: Multilevel Modeling Using R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
Price: 51.11 USD
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Description

Book Synopsis: 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.

Details

Are you ready to take your data analysis skills to the next level? Look no further than Multilevel Modeling Using R, Second Edition. This comprehensive guide provides all the tools you need to conduct multilevel data modeling using the powerful R software environment. Whether you’re a seasoned researcher or just starting out, this book will equip you with the knowledge and techniques to make your investigations more effective and insightful.

With its user-friendly approach, Multilevel Modeling Using R, Second Edition, is perfect for both beginners and experienced users. The authors not only explain the basics of multilevel models but also guide you through fitting these models using R. You’ll discover how to effectively analyze longitudinal data, visualize your findings with R’s graphical options, and create models for categorical dependent variables. Plus, you’ll learn the most up-to-date approaches for obtaining confidence intervals for your model parameters.

What sets this edition apart is its inclusion of new and exciting content. You’ll find a chapter dedicated to nonparametric and robust approaches, which expand your modeling options even further. Additionally, the book introduces the concept of multivariate multilevel models, providing a deeper understanding of complex data structures. These resources, along with discussions on micro-macro models and multilevel generalized additive models, make Multilevel Modeling Using R, Second Edition, a truly comprehensive resource.

Written by esteemed authors W. Holmes Finch, Jocelyn E. Bolin, and Ken Kelley, who are experts in the field of educational psychology, this updated edition will empower you with the necessary tools to launch your own successful investigations. Don’t miss out on this opportunity to enhance your research skills and gain valuable insights. Get your copy of Multilevel Modeling Using R, Second Edition, today!

Click here to order now and unlock the power of multilevel modeling with R!

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