The revised 6th edition by Pituch and Stevens is a very valuable and well-written text that provides students with all they need to understand and apply multivariate data analysis. The authors did a great job in revising the chapters, and the new coverage of binary logistic regression, multivariate multilevel modeling, and missing data analysis are a "must" for both applied researchers and graduate students. -Karin Schermelleh-Engel, Goethe University, Germany
This is a graduate level 3-credit, asynchronous online course. In this course we will examine a variety of statistical methods for multivariate data, including multivariate extensions of t-tests and analysis of variance, dimension reduction techniques such as principal component analysis, factor analysis, canonical correlation analysis, and classification and clustering methods.
SOLUTION OF APPLIED MULTIVARIATE STATISTICAL ANALYSIS SIXTH EDITION.zip
Following the EFA, two CFAs were conducted using the complete sample to test and compare both the proposed solution as specified by EFA and the original 25-item five-factor solution. The statistical quality of the models was assessed using two sets of measures. First, the overall goodness of fit was measured considering the following criteria: Standardized Root Mean Square Residual (SRMR) and Root Mean Square Error of Approximation (RMSEA) lower or equal to 0.08, Comparative-Fit Index (CFI) and Tucker-Lewis Index (TLI) higher or equal to 0.90. Additionally, the localised areas of strain were measured with the following criteria: standardised residuals lower or equal to 2.58 and general modification index analysis lower or equal to 4. 2ff7e9595c
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