MVSTATS Eighth Edition


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 eight edition:

  • 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 organizational domains.
  • 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 analytics
  • 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 outputs)

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Multivariate Data Analysis
Hair, Black, Babin and Anderson