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Multilevel Modeling Using R

Multilevel Modeling Using R

W. Holmes Finch, Jocelyn E. Bolin, Ken Kelley
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A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modelling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modelling 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 modelling 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. The book concludes with the Bayesian fitting of multilevel models. For those new to R, the appendix provides an introduction to this system that covers basic R knowledge necessary to run the models in the book. Through the R code and detailed explanations provided, this book gives you the tools to launch your own investigations in multilevel modelling and gain insight into your research.

Anno:
2014
Edizione:
1st Edition
Casa editrice:
Chapman & Hall/CRC Press
Lingua:
english
Pagine:
226
ISBN 10:
1466515864
ISBN 13:
9781466515864
Collana:
Statistics In The Social and Behavioral Sciences Series
File:
PDF, 3.16 MB
IPFS:
CID , CID Blake2b
english, 2014
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