The past decade has seen an explosion in the
interest and application of data analytics in both academic research and
decision-making in all types of organizations.
The emergence of Big Data has provided a newfound wealth of information
available to address questions in all fields of study. To meet that need, researchers have continued
their development of the traditional techniques as well as exploring new
avenues of analysis. The eighth edition
of Multivariate Data Analysis provides an updated perspective on data analysis
of all types of data as well as introducing some new perspectives and
techniques that are foundational in today’s world of analytics.
Among the specific additions and updates in the
- PLS_SEM -- New chapter on
partial least squares structural equation modeling (PLS-SEM), an emerging
technique with equal applicability for researchers in the academic and
- Integration of
the implications of Big Data into each of the chapters, providing some
understanding of the role of multivariate data analysis in this new era of
- Causal Inference and Multi-level/Panel Models -- Extended
discussions of emerging topics, including causal treatments/inference (i.e.,
causal analysis of non-experimental data as well as discussion of
propensity score models) along with multi-level and panel data models
(extending regression into new research areas and providing a framework
for cross-sectional/time-series analysis).
- Updates -- Updates in each
chapter of technical improvements (e.g., multiple imputation for missing
data treatments) as well as the merging of basic principles from the
fields of data mining and its applications.
- Additional SEM Topics -- In addition to
the new PLS-SEM chapter, the chapters on SEM have greater emphasis on
psychometrics and scale development, discussions on the use of reflective
versus formative scaling, describes an alternative approach for handing
interactions (orthogonal moderators), higher order models, multi-group
analyses, Bayesian SEM, and updated availability software availability
(e.g., Lavaan and SmartPLS). The
multi-group discussion also includes an alternative to partial metric
invariance when cross-group variance problems are small.
- Online resources -- For researchers including continued coverage from past editions of all of
the analyses from the latest versions of both SAS and SPSS (commands and
Drop us an
e-mail if you have a comment, suggestion
or online resource you would like to share.
Multivariate Data Analysis
Hair, Black, Babin and Anderson