Structural equation modeling (SEM) is a general, cross-sectional statistical modeling technique. The chapters in this book propose a Bayesian approach based on SEM; an examination of predictors and outcomes related to school climate using latent class analysis and the testing of specific effects and contrasts in three types of mediation models followed by a discussion on the common types o…
This edition, like previous editions, is written for those who use, rather than develop, advanced statistical methods. The focus is on conceptual understanding rather than proving results. The narrative and many examples are there to promote understanding, and a chapter on matrix algebra is included for those who need the extra help. Through- out the book, you will find output from SPSS (ve…
Multivariate analysis techniques are popular because they enable organizations to create knowledge and thereby improve their decision making. Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or objects under investigation. Thus, any simultaneous analysis of more than two variables can be loosely considered multivariat…
The statistical science has seen new paradigms and more complex and richer data sets. These include data on human genomics, social networks, huge climate and weather data, and, of course, high frequency financial and economic data.
The fourth edition of this book on Applied Multivariate Statistical Analysis offers a new sub-chapter on Variable Selection by using least absolute shrinkage and selection operator (LASSO) and its general form the so-called Elastic Net.
The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features. 1. A new Chapter 8 on Regression Models has been added. 2. Almost all numerical examples have been reproduced in MATLAB or R. The chapter on regression models focuses on a core business of multivariate statistical analysis. This contribution has not been subject of a prominent dis…
This volume derives from the 1996 Handbook of Organization Studies. Originally, the Handbook was launched primarily for a research audience. Since its launch, the book's success has led to many requests for a paperback edition, particularly in a format that instructors and students might use.
This book presents a basic introduction to structural equation modeling (SEM). Readers will find that we have followed our tradition of keeping examples rudi- mentary and easy to follow. The reader is provided with a review of correlation and covariance, followed by multiple regression, path, and factor analysis in order to better understand the building blocks of SEM. We then describe the …
For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of th…