This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The multivariate statistical methods covered in this text are factorial analysis of variance (ANOVA), analysis of covariance (ANCOVA), multivariat…
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 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 …
his is the fourth edition of the book Multivariate Statistical Methods: a Primer. The contents are similar to what was in the third edition of the book, with the main difference being the introduction of R code to do all of the analyses in the fourth edition. The version of R used for running the R-scripts (and the corresponding packages) is R 3.3.1. Also, the results obtained with the R c…
Statistical power analysis has revolutionized the ways in which behavioral and social scientists plan, conduct, and evaluate their research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications as software catches up with theory.