Like its bestselling predecessor, Multilevel Modeling Using R, Third 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. The third edition of the book includes several new topics that were not present in the second edition. Specifically, a new chapter has been included, focussing on fitting multilevel latent variable modeling in the R environment. With R, it is possible to fit a variety of latent variable models in the multilevel context, including factor analysis, structural models, item response theory, and latent class models. The third edition also includes new sections in chapter 11 describing two useful alternatives to standard multilevel models, fixed effects models and generalized estimating equations. These approaches are particularly useful with small samples and when the researcher is interested in modeling the correlation structure within higher level units (e.g., schools). The third edition also includes a new section on mediation modeling in the multilevel context, in chapter 11. 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.
本书责任者还有:(美)Lawrence L. Kupper、(美)Keith E. Muller、(美)Azhar Nizam。
Learning Goals Upon completing this book, readers should be able to: Learn to conduct numerous types of multivariate statistical analyses Find the best technique to use Understand Limitations to applications Learn how to use SPSS and SAS ...
For graduate and upper-level undergraduate marketing research courses.For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.
This market leader offers a readable introduction to the statistical analysis of multivariate observations.
3.1.8 The Value and the Valuation of Jobs In his research on job satisfaction , Arne L. Kalleberg ( 1977 ) of Indiana University discusses several approaches in occupational sociology . One group of researchers has sought to explain the ...
This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises...
Multivariate Data Analysis
7.3.3 Fitting Discrete-Time Hazards Regression Models Using PROC SURVEYLOGISTIC
Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations.
For graduate and upper-level undergraduate marketing research courses. For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.