Applied multivariate analysis:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Springer
2002
|
| Series: | Springer texts in statistics
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Physical Description: | XXIV, 693 S. graph. Darst. |
| ISBN: | 0387953477 |
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| 245 | 1 | 0 | |a Applied multivariate analysis |c Neil H. Timm |
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| 650 | 7 | |a Multivariate analyse |2 gtt | |
| 650 | 4 | |a Multivariate analysis | |
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Record in the Search Index
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| adam_text | Contents
Preface vii
Acknowledgments ix
List of Tables xix
List of Figures xxiii
1
1.1
1.2
1.3
2
2.1
2.2
a. Vectors
b. Vector Spaces
c. Vector Subspaces
2.3
a. Bases
b. Lengths, Distances, and Angles
c. Gram-Schmidt Orthogonalizatkm Process
d. Orthogonal Spaces
e. Vector Inequalities, Vector Norms, and Statistical Distance
xii Contents
2.4
a. Equality,
b. Matrix Transposition
c. Some Special Matrices
d. Trace and the Euclidean Matrix Norm
e.
f. Direct Sums
g. The Vec(-) and Vech(-) Operators
2.5
a. Rank and Inverse
b. Generalized Inverses
c. Determinants
2.6
a. Systems of Equations
b. Linear Transformations
c. Projection Transformations
d. Eigenvalues and Eigenvectors
e. Matrix Norms
f. Quadratic Forms and
g.
2.7
3
3.1
3.2
3.3
a. Properties of the Multivariate Normal Distribution
b. Estimating
c. The Matrix Normal Distribution
3.4
a. Chi-Square Distribution
b. The Wishart Distribution
3.5
a. The Univariate t and
b. Hotelling s T2 Distribution
c. The Beta Distribution
d. Multivariate
3.6
a. Regression, ANOVA, and ANCOVA Models
b. Multivariate Regression, MANOVA, and MANCOVA Models
c. The Seemingly Unrelated Regression
d. The General MANOVA Model (GMANOVA)
3.7
3.8
a. Tests of Covariance Matrices
Contents xiii
b.
c. Testing for a Specific Covariance Matrix
d. Testing for Compound Symmetry
e. Tests of Sphericity
f. Tests of Independence
g. Tests for Linear Structure
3.9
a. Two-Sample Case, Si
b. Two-Sample Case, Si ^
c. Two-Sample Case, Nonnormality
d. Profile Analysis, One Group
e. Profile Analysis, Two Groups
f. Profile Analysis,
3.10
a. Univariate One-Group Profile Analysis
b. Univariate Two-Group Profile Analysis
3.11
Multívariaíe
4.1
4.2
a. Multiple Linear Regression
b. Multivariate Regression Estimation and Testing Hypotheses
c. Multivariate Influence Measures
d. Measures of Association, Variable Selection and Lack-of-Fit Tests
e. Simultaneous Confidence Sets for a New Observation ynew
and the Elements of B
f
ror of Prediction in Multivariate Regression
g. Exogeniety in Regression
4.3
4.4
a. One-Way MANOVA
b. One-WayMANCOVA
c. Simultaneous Test Procedures (STP) for One-Way MANOVA
/MANCOVA
4.5
a. MANOVA (Example
b. MANCOVA (Example
4.6
4.7
4.8
a. Two-Way MANOVA with Interaction
b. Additive Two-Way MANOVA
c. Two-Way MANCOVA
xiv Contents
d. Tests of
4.9
a. Two-Way MANOVA (Example
b. Two-Way MANCOVA (Example
4.10 Nonorthogonal
a. Nonorthogonal Two-Way MANOVA Designs with and Without
Empty Cells, and Interaction
b. Additive Two-Way MANOVA Designs With Empty Cells
4.11
4.12
4.13
a. Nested Design (Example
b. Latin Square Design (Example
4.14
a. One-Way Repeated Measures Design
b. Extended Linear Hypotheses
4.15
a. Repeated Measures (Example
b. Extended Linear Hypotheses (Example
4.16
4.17
4.18
5
5.1
5.2
a. Estimation and Hypothesis Testing
b. Prediction
5.3
5.4
5.5
5.6
a. Overview
b. Estimation and Hypothesis Testing
c. Test of Fit
d. Subsets of Covariates
e. GMANOVA vs
f.
5.7
a. One Group Design (Example
b. Two Group Design (Example
. 5.8
5.9
5.10
5.11
Contents xv
5.12 The Multivariate
5.13
5.14
5.15
Multivariate
6.1
6.2
a. Model Specification
b. Estimating the Parameters
c. Hypothesis Testing
6.3
a. Model Specification
b. Covariance Structures and Model Fit
c. Model Checking
d. Balanced Variance Component Experimental Design Models
e. Multilevel Hierarchical Models
f. Prediction
6.4
a. Random Coefficient Regression (Example
b. Generalized Randomized Block Design (Example
c. Repeated Measurements (Example
d. HLM Model (Example
6.5
a. Model Specification
b. Hypothesis Testing
c. Evaluating Expected Mean Square
d. Estimating the Mean
e. Repeated Measurements Model
6.6
a. Two-way Mixed MANOVA
b. Multivariate Split-Plot Design
6.7
6.8
a. Double Multivariate MANOVA (Example
b. Split-Plot Design (Example
6.9
6.10
Discriminant and Classification Analysis
7.1
7.2
a. Fisher s Linear Discriminant Function
b. Testing Discriminant Function Coefficients
c. Classification Rules
xvi Contents
d. Evaluating Classification Rules
7.3
a. Egyptian Skull Data (Example
b. Brain Size (Example
7.4
a. Fisher s Linear Discriminant Function
b. Testing Discriminant Functions for Significance
c. Variable Selection
d. Classification Rules
e. Logistic Discrimination and Other Topics
7.5
8
Factor Analysis
8.1
8.2
a. Population Model for PCA
b. Number of Components and Component Structure
c. Principal Components with Covariates
d. Sample PCA
e. Plotting Components
f. Additional Comments
g. Outlier Detection
8.3
a. Test Battery (Example
b. Semantic Differential Ratings (Example
c. Performance Assessment Program (Example
8.4
a. Tests Using the Covariance Matrix
b. Tests Using a Correlation Matrix
8.5
a. GMANOVAModel
b. ThePCAModel
8.6
8.7
a. Population Model for CCA
b. Sample CCA
c. Tests of Significance
d. Association and Redundancy
e. Partial, Part and Bipartial Canonical Correlation
f
g. Variable Selection and Generalized Constrained CCA
8.8
a. Rohwer CCA (Example
b. Partial and Part CCA (Example
Contents xvii
8.9
a. Population Model for EFA
b. Estimating Model Parameters
c. Determining Model Fit
d. Factor Rotation
e. Estimating Factor Scores
f. Additional Comments
8.10
a. Performance Assessment Program (PAP
b.
c. Shin (Example
9
9.1
9.2
a. Dissimilarity Measures
b. Similarity Measures
c. Clustering Variables
9.3
a. Agglomerative Hierarchical Clustering Methods
b. Nonhierarchical Clustering Methods
c. Number of Clusters
d. Additional Comments
9.4
a. Protein Consumption (Example
b. Nonhierarchical Method (Example
c. Teacher Perception (Example
d. Cedar Project (Example
9.5
a. Classical Metric Scaling
b. Nonmetric Scaling
c. Additional Comments
9.6
a. Classical Metric Scaling (Example
b. Teacher Perception (Example
c. Nation (Example
10
10.1
10.2
10.3
10.4
a. Performance Assessment
b. Performance Assessment 5-Factor Model (Example
10.5
xviii Contents
10.6
a. Community Structure and Industrial Conflict (Example
b. Nonrecursive Model (Example
10.7
10.8
10.9
10.10
Appendix
References
Author Index
Subject Index
This textbook provides a broad overview of the basic theory and methods of applied multivari-
ate analysis. The presentation integrates theory and practice including both the analysis of for¬
mal linear multivariate models and exploratory data analysis techniques. Each chapter contains
the development of basic theoretical results with numerous applications illustrated using exam¬
ples from the social and behavioral sciences as well as from other disciplines. All examples are
analyzed using
The book includes an overview of vectors, matrices, multivariate distribution theory, and multi¬
variate linear models. Topics discussed include multivariate regression, multivariate analysis of
variance for fixed and mixed models, seemingly unrelated regression models, and repeated
measurement models. While standard procedures for estimating model parameters and testing
multivariate hypotheses, as well as simultaneous test procedures, are discussed and illustrated in
the text, the text also includes tests of multivariate normality with chi-square and beta plots, tests
of multivariate nonadditivily, tests of covariance structure, tests of nonnested hypotheses, and the
assessment of model assumptions. Other topics discussed include discriminant and classification
analysis, principal component analysis, canonical correlation analysis, exploratory factor analy¬
sis, cluster analysis, multidimensional scaling, and structural equation modeling.
The text should appeal to practitioners, researchers, and applied statisticians. It may be used in
a one-semester course in applied multivariate analysis for practitioners and researchers, or as a
two-semester course for majors in applied statistics. Because most data analyzed in the social
and behavioral sciences and other disciplines involve many continuous variables, the techniques
and examples discussed in the book should be helpful in the analysis of multivariate data using
SAS.
|
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| spelling | Timm, Neil H. Verfasser (DE-588)124033717 aut Applied multivariate analysis Neil H. Timm New York [u.a.] Springer 2002 XXIV, 693 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer texts in statistics Analyse multivariée Análise multivariada larpcal Multivariate analyse gtt Multivariate analysis Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf 1\p (DE-588)4151278-9 Einführung gnd-content Multivariate Analyse (DE-588)4040708-1 s DE-604 Digitalisierung UBPassau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009842110&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009842110&sequence=000002&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Timm, Neil H. Applied multivariate analysis Analyse multivariée Análise multivariada larpcal Multivariate analyse gtt Multivariate analysis Multivariate Analyse (DE-588)4040708-1 gnd |
| subject_GND | (DE-588)4040708-1 (DE-588)4151278-9 |
| title | Applied multivariate analysis |
| title_auth | Applied multivariate analysis |
| title_exact_search | Applied multivariate analysis |
| title_full | Applied multivariate analysis Neil H. Timm |
| title_fullStr | Applied multivariate analysis Neil H. Timm |
| title_full_unstemmed | Applied multivariate analysis Neil H. Timm |
| title_short | Applied multivariate analysis |
| title_sort | applied multivariate analysis |
| topic | Analyse multivariée Análise multivariada larpcal Multivariate analyse gtt Multivariate analysis Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Analyse multivariée Análise multivariada Multivariate analyse Multivariate analysis Multivariate Analyse Einführung |
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