Applied Multivariate Statistical Concepts

This second edition of Applied Multivariate Statistical Concepts covers the classic and

cutting-edge multivariate techniques used in today's research.

Through clear writing and engaging pedagogy and examples using real data,

Hahs-Vaughn walks students through the most used methods to learn why and how to

apply each technique. A conceptual approach with a higher than usual text-to-formula

ratio helps readers master key concepts so they can implement and interpret results

generated by today's sophisticated software. Additional features include examples

using real data from the social sciences; templates for writing research questions and

results that provide manuscript-ready models; step-by-step instructions on using R

and SPSS statistical software with screenshots and annotated output; clear coverage of

assumptions, including how to test them and the effects of their violation; and conceptual,

computational, and interpretative example problems that mirror the real-world

problems students encounter in their studies and careers. This edition features expanded

coverage of topics, such as propensity score analysis, path analysis and confirmatory

factor analysis, and centering, moderation effects, and power as related to multilevel

modelling. New topics are introduced, such as addressing missing data and latent class

analysis, while each chapter features an introduction to using R statistical software.

This textbook is ideal for courses on multivariate statistics/analysis/design, advanced

statistics, and quantitative techniques, as well as for graduate students broadly in social

sciences, education, and behavioral sciences. It also appeals to researchers with no

training in multivariate methods.