Multilevel modeling using R / W. Holmes Finch, Ball State University, Muncie, Indiana, USA, Jocelyn E. Bolin, Ball State University, Muncie, Indiana, USA, Ken Kelley, University of Notre Dame, Notre Dame, Indiana, USA
Material type:
TextSeries: Statistics in the social and behavioral sciences seriesPublisher: Boca Raton, FL : CRC Press, Taylor & Francis Group, [2014]Description: xiii, 216 pages ; 24 cmContent type: - text
- unmediated
- volume
- 9781138469334
- HA31.35 .F56 2014
| Item type | Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|
| Books - Printed | PERPUSTAKAAN GUNASAMA HAB PENDIDIKAN TINGGI PAGOH Main Library General | HA31.35 .F56 2014 (Browse shelf(Opens below)) | Available | 0000001937 |
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| HA31.3 .S33 1986 Understanding regression analysis : an introductory guide / | HA31.3 .S33 1986 Understanding regression analysis : an introductory guide / | HA31.3 .W74 2009 Modern regression techniques using R : a practical guide for students and researchers / | HA31.35 .F56 2014 Multilevel modeling using R / | HA31.35 .H32 2011 Multivariate general linear models / | HA31.35 .W37 2008 Applied statistics : from bivariate through multivariate techniques / | HA31.35 .W37 2008 Applied statistics : from bivariate through multivariate techniques / |
"This book presents the theory and practice of major multilevel modeling techniques in a variety of contexts using R as the software tool. It describes the applications and extensions of multilevel modeling with special emphasis on the use of R to conduct the analyses and interpret the resulting output. The book is designed for researchers, data analysts, and upper-level undergraduate and graduate students taking a course on multilevel modeling or statistical modeling. "-- Provided by publisher
Includes bibliographical references and index
1. Linear models -- 2. Introduction to multilevel data structure -- 3. Fitting two-level models in R -- 4. Models of three and more levels -- 5. Longitudinal data analysis using multilevel models -- 6. Graphing data in multilevel contexts -- 7. Brief introduction to generalized linear models -- 8. Multilevel generalized linear models -- 9. Bayesian multilevel modeling
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