Much social and behavioral research involves hierarchical data structures. The effects of school characteristics on students, how differences in government policies from country to country influence demographic relations within them, and how individuals exposed to different environmental conditions develop over time are a few examples. This introductory text explicates the theory and use of hierarchical linear models through rich illustrative examples and lucid explanations.
Guide and Applications G. David Garson. Hierarchical Linear Modeling Guide and Applications G. David Garson Editor North Carolina State University BRIEF CONTENTS Preface xiii About the Editor xv About the.
HLM 6: Hierarchical Linear and Nonlinear Modeling
The intervention for low - birth - weight children is described by Brooks - Gunn , Liaw , and Klebanov ( 1992 ) and Hill , Brooks - Gunn , and Waldfogel ( 2003 ) . Imbalance plots such as Figure 10.3 are commonly used ; see Hansen ...
This book summarizes developments within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to advanced statistical modelling including generalized linear models ...
... controlling for variable X. It is analogous to the usual intraclass correlation coefficient , but now controlling for X. The formula for the ( non - residual , or raw ) intraclass correlation coefficient was just the same ...
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded ...
In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data (pp. ... Sample size requirements for 2-level designs in educational research. ... Complex sample data in structural equation modeling.
Applications in STATA®, IBM® SPSS®, SAS®, R, & HLMTM G. David Garson. addition to the editor, and the five chapters by the editor use different examples and have different content.) Garson, G. David. (2013b).
A website for the book includes the data and the statistical code (both R and Stata) used for all of the presented analyses.
Put simply, this is perhaps the most engaging introductory statistics textbook I have ever read. [It] is a natural choice for an introductory undergraduate course in applied Bayesian statistics.