Applied Multivariate Statistics for the Social Sciences

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A01=James P. Stevens
A01=Keenan A. Pituch
advanced statistical inference
Author_James P. Stevens
Author_Keenan A. Pituch
Canonical Correlation
Canonical Variates
Category=JHBC
CFA Model
covariance structure analysis
Data Set
dependent
Descriptive Discriminant Analysis
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
eta
exploratory factor analysis
Fit Index
hierarchical modelling
hypothesis
largest
Largest Canonical Correlation
Latent Variable Path Model
Memory Training Group
Missing Data
Model Fit
multivariate data analysis techniques
Multivariate Null Hypothesis
Multivariate Test
Multivariate Test Statistic
partial
PROC MIXED DATA
quantitative research methods
Randomly Assigned
repeated measures statistics
root
roys
Specific Indirect Effect
Sphericity Assumption
SPSS Command
SPSS Control Line
SPSS MANOVA
SPSS Syntax
squared
Student SES
test
Test Irrelevant Thinking
Univariate ANOVA

Product details

  • ISBN 9780415836661
  • Weight: 1420g
  • Dimensions: 178 x 254mm
  • Publication Date: 23 Nov 2015
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally.

Features new to this edition include:

  • NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure
  • NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings
  • NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles
  • NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data
  • Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results
  • NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach
  • Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3)
  • A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises)

Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

Keenan Pituch is Associate Professor in the Quantitative Methods Area of the Department of Educational Psychology at the University of Texas at Austin.

James P Stevens is Professor Emeritus at University of Cincinatti.

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