GLM Multivariate, MANOVA, & Canonical Correlation 2015 (Statistical Associates Blue Book Series 11)

GLM MULTIVARIATE, MANOVA, & CANONICAL CORRELATION Overview

An illustrated tutorial and introduction to multivariate general linear models, MANOVA, MANCOVA, and linear and nonlinear canonical correlation, using SPSS, SAS, and Stata for examples. Suitable for introductory graduate-level study.

The 2015 edition is a major update to the 2012 edition. Among the new features are these:

* Was 59 pages, now book length (270 pages total)
* Has over 130 new illustrations
* Now covers Stata and SAS as well as SPSS
* Shows commands and options needed for similar results across packages.
* Totally revised with new examples
* New coverage detailing assumptions and testing for them.
* New coverage of 29 Frequently Asked Questions.
* New coverage of nonliner canonical correlation.
* Links to all datasets used in the text.

Below is the unformatted table of contents.

MULTIVARIATE GLM, MANOVA, AND MANCOVA 1
Data examples for MANOVA 10
MANOVA & MANCOVA 10
GLM in statistics packages 12
SPSS 12
SAS 12
Stata 12
Key coefficients in multivariate GLM 13
F tests 13
t tests 13
Partial eta-square 14
R-Square 14
Omega-square 14
Multivariate GLM in SPSS 15
SPSS input 15
The main multivariate GLM dialog 15
The Model dialog 16
The Options dialog 18
The Contrasts dialog 19
The Plots dialog 20
The Save dialog 21
The Post hoc dialog 22
The Bootstrap dialog 23
SPSS syntax 24
SPSS output 25
Multivariate significance tests 25
Significance tests of between-subjects effects (F tests) 28
Parameter estimates 30
Differences in statistical inference 32
Lack of fit tests 32
Spread-versus-level plots 36
Residual plots 38
Outlier diagnostics 40
Analysis of covariance 40
Estimated marginal means 40
Profile plots 43
Pairwise comparison tables 46
Multiple comparison and post-hoc tests 48
Contrast tests 50
Multivariate GLM in SAS 53
SAS input 53
SAS Output 55
Multivariate significance tests 55
Significance tests of between-subjects effects 56
Parameter Estimates 60
Lack of fit tests 61
Spread-versus-level plots 61
Residual plots 63
Outlier diagnostics 68
Analysis of covariance 73
Estimated marginal means 74
Profile Plots 75
Pairwise comparison tables 76
Multiple comparison and post-hoc tests 80
Contrast tests 82
Multivariate GLM in Stata 85
Stata input 85
Stata output 87
Multivariate significance tests 87
Significance tests of between-subjects effects (F tests) 89
Parameter Estimates 91
Lack of fit tests 91
Spread-versus-level plots 91
Residual plots 95
Outlier diagnostics 101
Analysis of covariance 108
Estimated marginal means 110
Profile Plots 111
Pairwise comparison tables 113
Multiple comparison and post-hoc tests 115
Contrast tests 119
GLM multivariate assumptions 123
Measurement level 123
Observations are independent of one another 123
Random sampling 124
Homogeneity of error variances 124
Levene's test 125
SPSS 126
SAS 127
Stata 128
Homogeneity of regressions 130
Overview 130
SPSS 131
SAS 132
Stata 133
Homogeneity of covariances 135
Box's M test 135
SPSS 136
SAS 137
Stata 138
Sphericity 139
Bartlett's test of sphericity 139
SPSS 140
SAS 141
Stata 142
Low measurement error of the covariates 142
Similar group sizes 143
Adequate group sizes 143
Appropriate sums of squares 143
SPSS 144
SAS 144
Stata 144
Random normal residuals 145
Linearity 145
Multivariate normal distribution 145
No outliers 146
GLM frequently asked questions 146
Why can't I just use multiple univariate ANOVA tests rather than MANOVA? 146
How do I write up the results of my MANOVA analysis? 147
How many dependent variables can I have in MANOVA? 148
Can I enter just one dependent variable in MANOVA? 149
Is there a limit on the number of covariates which can be included in a multiple analysis of variance? 149
Explain the syntax for MANOVA in SPSS 149
What is analysis of residuals for in MANOVA 150
AND 120 MORE PAGES OF TOPICS