More comprehensive than other texts, this new book covers the
classic and cutting edge multivariate techniques used in today's
research. Ideal for courses on multivariate
statistics/analysis/design, advanced statistics or quantitative
techniques taught in psychology, education, sociology, and
business, the book also appeals to researchers with no training in
multivariate methods. 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 reader's master key concepts so they can implement and
interpret results generated by today's sophisticated software.
Annotated screenshots from SPSS and other packages are integrated
throughout. Designed for course flexibility, after the first 4
chapters, instructors can use chapters in any sequence or
combination to fit the needs of their students. Each chapter
includes a 'mathematical snapshot' that highlights the technical
components of each procedure, so only the most crucial equations
are included. Highlights include: -Outlines, key concepts, and
vignettes related to key concepts preview what's to come in each
chapter -Examples using real data from education, psychology, and
other social sciences illustrate key concepts -Extensive coverage
of assumptions including tables, the effects of their violation,
and how to test for each technique -Conceptual, computational, and
interpretative problems mirror the real-world problems students
encounter in their studies and careers -A focus on data screening
and power analysis with attention on the special needs of each
particular method -Instructions for using SPSS via screenshots and
annotated output along with HLM, Mplus, LISREL, and G*Power where
appropriate, to demonstrate how to interpret results -Templates for
writing research questions and APA-style write-ups of results which
serve as models -Propensity score analysis chapter that
demonstrates the use of this increasingly popular technique -A
review of matrix algebra for those who want an introduction
(prerequisites include an introduction to factorial ANOVA, ANCOVA,
and simple linear regression, but knowledge of matrix algebra is
not assumed) -www.routledge.com/9780415842365 provides the text's
datasets preformatted for use in SPSS and other statistical
packages for readers, as well as answers to all chapter problems,
Power Points, and test items for instructors
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