Table Of ContentMethods of Multivariate Analysis
Second Edition
Methods of Multivariate Analysis
Second Edition
ALVINC.RENCHER
BrighamYoungUniversity
AJOHNWILEY&SONS,INC.PUBLICATION
∞
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LibraryofCongressCataloging-in-PublicationData
Rencher,AlvinC.,1934–
Methodsofmultivariateanalysis/AlvinC.Rencher.—2nded.
p. cm.—(Wileyseriesinprobabilityandmathematicalstatistics)
“AWiley-Intersciencepublication.”
Includesbibliographicalreferencesandindex.
ISBN0-471-41889-7(cloth)
1. Multivariateanalysis. I. Title. II. Series.
QA278.R452001
519.5(cid:2)35—dc21 2001046735
PrintedintheUnitedStatesofAmerica
10 9 8 7 6 5 4 3 2 1
Contents
1. Introduction 1
1.1 WhyMultivariateAnalysis?, 1
1.2 Prerequisites, 3
1.3 Objectives, 3
1.4 BasicTypesofDataandAnalysis, 3
2. MatrixAlgebra 5
2.1 Introduction, 5
2.2 NotationandBasicDefinitions, 5
2.2.1 Matrices,Vectors,andScalars, 5
2.2.2 EqualityofVectorsandMatrices, 7
2.2.3 TransposeandSymmetricMatrices, 7
2.2.4 SpecialMatrices, 8
2.3 Operations, 9
2.3.1 SummationandProductNotation, 9
2.3.2 AdditionofMatricesandVectors, 10
2.3.3 MultiplicationofMatricesandVectors, 11
2.4 PartitionedMatrices, 20
2.5 Rank, 22
2.6 Inverse, 23
2.7 PositiveDefiniteMatrices, 25
2.8 Determinants, 26
2.9 Trace, 30
2.10 OrthogonalVectorsandMatrices, 31
2.11 EigenvaluesandEigenvectors, 32
2.11.1 Definition, 32
2.11.2 I+AandI−A, 33
2.11.3 tr(A)and|A|, 34
2.11.4 PositiveDefiniteandSemidefiniteMatrices, 34
2.11.5 TheProductAB, 35
2.11.6 SymmetricMatrix, 35
v
vi CONTENTS
2.11.7 SpectralDecomposition, 35
2.11.8 SquareRootMatrix, 36
2.11.9 SquareMatricesandInverseMatrices, 36
2.11.10 SingularValueDecomposition, 36
3. CharacterizingandDisplayingMultivariateData 43
3.1 MeanandVarianceofaUnivariateRandomVariable, 43
3.2 CovarianceandCorrelationofBivariateRandomVariables, 45
3.2.1 Covariance, 45
3.2.2 Correlation, 49
3.3 ScatterPlotsofBivariateSamples, 50
3.4 GraphicalDisplaysforMultivariateSamples, 52
3.5 MeanVectors, 53
3.6 CovarianceMatrices, 57
3.7 CorrelationMatrices, 60
3.8 MeanVectorsandCovarianceMatricesforSubsetsof
Variables, 62
3.8.1 TwoSubsets, 62
3.8.2 ThreeorMoreSubsets, 64
3.9 LinearCombinationsofVariables, 66
3.9.1 SampleProperties, 66
3.9.2 PopulationProperties, 72
3.10 MeasuresofOverallVariability, 73
3.11 EstimationofMissingValues, 74
3.12 DistancebetweenVectors, 76
4. TheMultivariateNormalDistribution 82
4.1 MultivariateNormalDensityFunction, 82
4.1.1 UnivariateNormalDensity, 82
4.1.2 MultivariateNormalDensity, 83
4.1.3 GeneralizedPopulationVariance, 83
4.1.4 DiversityofApplicationsoftheMultivariateNormal, 85
4.2 PropertiesofMultivariateNormalRandomVariables, 85
4.3 EstimationintheMultivariateNormal, 90
4.3.1 MaximumLikelihoodEstimation, 90
4.3.2 DistributionofyandS, 91
4.4 AssessingMultivariateNormality, 92
4.4.1 InvestigatingUnivariateNormality, 92
4.4.2 InvestigatingMultivariateNormality, 96
CONTENTS vii
4.5 Outliers, 99
4.5.1 OutliersinUnivariateSamples, 100
4.5.2 OutliersinMultivariateSamples, 101
5. TestsonOneorTwoMeanVectors 112
5.1 MultivariateversusUnivariateTests, 112
5.2 Testson(cid:1)with(cid:2)Known, 113
5.2.1 ReviewofUnivariateTestfor H :µ=µ
0 0
withσ Known, 113
5.2.2 MultivariateTestfor H :(cid:1)=(cid:1) with(cid:2)Known, 114
0 0
5.3 Testson(cid:1)When(cid:2)IsUnknown, 117
5.3.1 ReviewofUnivariatet-Testfor H :µ=µ withσ
0 0
Unknown, 117
5.3.2 Hotelling’sT2-Testfor H :(cid:1)=(cid:1) with(cid:2)Unknown, 117
0 0
5.4 ComparingTwoMeanVectors, 121
5.4.1 ReviewofUnivariateTwo-Samplet-Test, 121
5.4.2 MultivariateTwo-SampleT2-Test, 122
5.4.3 LikelihoodRatioTests, 126
5.5 TestsonIndividualVariablesConditionalonRejectionof H by
0
theT2-Test, 126
5.6 ComputationofT2, 130
5.6.1 ObtainingT2fromaMANOVAProgram, 130
5.6.2 ObtainingT2fromMultipleRegression, 130
5.7 PairedObservationsTest, 132
5.7.1 UnivariateCase, 132
5.7.2 MultivariateCase, 134
5.8 TestforAdditionalInformation, 136
5.9 ProfileAnalysis, 139
5.9.1 One-SampleProfileAnalysis, 139
5.9.2 Two-SampleProfileAnalysis, 141
6. MultivariateAnalysisofVariance 156
6.1 One-WayModels, 156
6.1.1 UnivariateOne-WayAnalysisofVariance(ANOVA), 156
6.1.2 MultivariateOne-WayAnalysisofVarianceModel
(MANOVA), 158
6.1.3 Wilks’TestStatistic, 161
6.1.4 Roy’sTest, 164
6.1.5 PillaiandLawley–HotellingTests, 166
viii CONTENTS
6.1.6 UnbalancedOne-WayMANOVA, 168
6.1.7 SummaryoftheFourTestsandRelationshiptoT2, 168
6.1.8 MeasuresofMultivariateAssociation, 173
6.2 ComparisonoftheFourManovaTestStatistics, 176
6.3 Contrasts, 178
6.3.1 UnivariateContrasts, 178
6.3.2 MultivariateContrasts, 180
6.4 TestsonIndividualVariablesFollowingRejectionof H bythe
0
OverallMANOVATest, 183
6.5 Two-WayClassification, 186
6.5.1 ReviewofUnivariateTwo-WayANOVA, 186
6.5.2 MultivariateTwo-WayMANOVA, 188
6.6 OtherModels, 195
6.6.1 HigherOrderFixedEffects, 195
6.6.2 MixedModels, 196
6.7 CheckingontheAssumptions, 198
6.8 ProfileAnalysis, 199
6.9 RepeatedMeasuresDesigns, 204
6.9.1 Multivariatevs.UnivariateApproach, 204
6.9.2 One-SampleRepeatedMeasuresModel, 208
6.9.3 k-SampleRepeatedMeasuresModel, 211
6.9.4 ComputationofRepeatedMeasuresTests, 212
6.9.5 RepeatedMeasureswithTwoWithin-Subjects
FactorsandOneBetween-SubjectsFactor, 213
6.9.6 RepeatedMeasureswithTwoWithin-Subjects
FactorsandTwoBetween-SubjectsFactors, 219
6.9.7 AdditionalTopics, 221
6.10 GrowthCurves, 221
6.10.1 GrowthCurveforOneSample, 221
6.10.2 GrowthCurvesforSeveralSamples, 229
6.10.3 AdditionalTopics, 230
6.11 TestsonaSubvector, 231
6.11.1 TestforAdditionalInformation, 231
6.11.2 StepwiseSelectionofVariables, 233
7. TestsonCovarianceMatrices 248
7.1 Introduction, 248
7.2 TestingaSpecifiedPatternfor(cid:2), 248
7.2.1 Testing H : (cid:2)=(cid:2) , 248
0 0
CONTENTS ix
7.2.2 TestingSphericity, 250
7.2.3 Testing H : (cid:2)=σ2[(1−ρ)I+ρJ], 252
0
7.3 TestsComparingCovarianceMatrices, 254
7.3.1 UnivariateTestsofEqualityofVariances, 254
7.3.2 MultivariateTestsofEqualityofCovarianceMatrices, 255
7.4 TestsofIndependence, 259
7.4.1 IndependenceofTwoSubvectors, 259
7.4.2 IndependenceofSeveralSubvectors, 261
7.4.3 TestforIndependenceofAllVariables, 265
8. DiscriminantAnalysis:DescriptionofGroupSeparation 270
8.1 Introduction, 270
8.2 TheDiscriminantFunctionforTwoGroups, 271
8.3 RelationshipbetweenTwo-GroupDiscriminantAnalysisand
MultipleRegression, 275
8.4 DiscriminantAnalysisforSeveralGroups, 277
8.4.1 DiscriminantFunctions, 277
8.4.2 AMeasureofAssociationforDiscriminantFunctions, 282
8.5 StandardizedDiscriminantFunctions, 282
8.6 TestsofSignificance, 284
8.6.1 TestsfortheTwo-GroupCase, 284
8.6.2 TestsfortheSeveral-GroupCase, 285
8.7 InterpretationofDiscriminantFunctions, 288
8.7.1 StandardizedCoefficients, 289
8.7.2 Partial F-Values, 290
8.7.3 CorrelationsbetweenVariablesandDiscriminant
Functions, 291
8.7.4 Rotation, 291
8.8 ScatterPlots, 291
8.9 StepwiseSelectionofVariables, 293
9. ClassificationAnalysis:AllocationofObservationstoGroups 299
9.1 Introduction, 299
9.2 ClassificationintoTwoGroups, 300
9.3 ClassificationintoSeveralGroups, 304
9.3.1 EqualPopulationCovarianceMatrices:Linear
ClassificationFunctions, 304
9.3.2 UnequalPopulationCovarianceMatrices:Quadratic
ClassificationFunctions, 306
Description:Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen.When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather tha