Permutation tests for complex data: theory, applications and software
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Chichester
Wiley
2010
|
| Edition: | 1. publ. |
| Series: | Wiley series in probability and statistics
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. [387] - 407 |
| Physical Description: | XXI, 417 S. Ill., graph. Darst. |
| ISBN: | 0470516410 9780470516416 |
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| adam_text | PERMUTATION TESTS FOR COMPLEX DATA THEORY, APPLICATIONS AND SOFTWARE
FORTUNATO PESARIN * LUIGI SALMASO UNIVERSITY OFPADUA, ITALY TECHNISCHE
INFORMATIONSBIBUOTHEK UNIVERSITATSBIBLIOTHEK HANNOVER V * WILEY A JOHN
WILEY AND SONS, LTD., PUBLICATION CONTENTS PREFACE XV NOTATION AND
ABBREVIATIONS XIX 1 INTRODUCTION 1 1. J ON PERMUTATION ANALYSIS 1 1.2
THE PERMUTATION TESTING PRINCIPLE 4 1.2.1 NONPARAMETRIC FAMILY OF
DISTRIBUTIONS 4 1.2.2 THE PERMUTATION TESTING PRINCIPLE 5 1.3
PERMUTATION APPROACHES 7 1.4 WHEN AND WHY CONDITIONING IS APPROPRIATE 7
1.5 RANDOMIZATION AND PERMUTATION 9 1.6 COMPUTATIONAL ASPECTS 10 1.7
BASIC NOTATION 11 1.8 A PROBLEM WITH PAIRED OBSERVATIONS 13 1.8.1
MODELLING RESPONSES 13 1.8.2 SYMMETRY INDUCED BY EXCHANGEABILITY 15
1.8.3 FURTHERASPECTS 15 1.8.4 THE STUDENT S T-PAIRED SOLUTION 16 1.8.5
THE SIGNED RANK TEST SOLUTION 17 1.8.6 THE MCNEMAR SOLUTION 18 1.9 THE
PERMUTATION SOLUTION 18 1.9.1 GENERAL ASPECTS 18 7.9.2 THE PERMUTATION
SAMPLE SPACE 19 1.9.3 THE CONDITIONAL MONTE CARLOMETHOD 20 1.9.4
APPROXIMATING THE PERMUTATION DISTRIBUTION 22 1.9.5 PROBLEMS AND
EXERCISES 23 1.10 A TWO-SAMPLE PROBLEM 23 1.10.1 MODELLING RESPONSES 24
1.10.2 THE STUDENT T SOLUTION 25 1.10.3 THE PERMUTATION SOLUTION 25
1.10.4 RANK SOLUTIONS 28 1.10.5 PROBLEMS AND EXERCISES 28 1.11
ONE-WAYANOVA 29 1.11.1 MODELLING RESPONSES 29 7.77.2 PERMUTATION
SOLUTIONS 30 7.77.3 PROBLEMS AND EXERCISES 32 VIII CONTENTS 2 THEORY OF
ONE-DIMENSIONAL PERMUTATION TESTS 33 2.1 INTRODUCTION 33 2.1.1 NOTATION
ANDBASICASSUMPTIONS 33 2.1.2 THE CONDITIONAL REFERENCE SPACE 35 2.1.3
CONDITIONING ON A SET OF SUFFICIENT STATISTICS 39 2.2 DEFINITION OF
PERMUTATION TESTS 41 2.2./ GENERAL ASPECTS 41 2.2.2 RANDOMIZED
PERMUTATION TESTS 42 2.2.3 NON-RANDOMIZEDPERMUTATION TESTS 43 2.2.4 THE
P-VALUE 43 2.2.5 ACMC ALGORITHMFORESTIMATING THE P-VALUE 44 2.3 SOME
USEFUL TEST STATISTICS 45 2.4 EQUIVALENCE OF PERMUTATION STATISTICS 47
2.4.1 SOME EXAMPLES 49 2.4.2 PROBLEMS AND EXERCISES 50 2.5 ARGUMENTS FOR
SELECTING PERMUTATION TESTS 51 2.6 EXAMPLES OF ONE-SAMPLE PROBLEMS 53
2.6.1 A PROBLEM WITH REPEATED OBSERVATIONS 59 2.6.2 PROBLEMSAND
EXERCISES 63 2.7 EXAMPLES OF MULTI-SAMPLE PROBLEMS 64 2.8 ANALYSIS
OFORDERED CATEGORICAL VARIABLES 74 2.8.1 GENERAL ASPECTS 74 2.8.2 A
SOLUTION BASED ON SCORE TRANSFORMATIONS 76 2.8.3 TYPICAL GOODNESS-OF-EIT
SOLUTIONS 77 2.8.4 EXTENSION TO NON-DOMINANCE ALTERNATIVES AND C GROUPS
79 2.9 PROBLEMS AND EXERCISES 80 3 FURTHER PROPERTIES OF PERMUTATION
TESTS 83 3.1 UNBIASEDNESS OF TWO-SAMPLE TESTS 83 3.1.1
ONE-SIDEDALTERNATIVES 83 3.1.2 TWO-SIDEDALTERNATIVES 90 3.2 POWER
FUNCTIONS OF PERMUTATION TESTS 93 3.2.1 DEFINITION ANDALGORITHMFOR THE
CONDITIONAL POWER 93 3.2.2 THE EMPIRICAL CONDITIONALROC CURVE 97 3.2.3
DEFINITION ANDALGORITHMFOR THE UNCONDITIONAL POWER: FIXED EFFECTS 97
3.2.4 UNCONDITIONAL POWER; RANDOM EFFECTS 98 3.2.5 COMMENTS ON POWER
FUNCTIONS 98 3.3 CONSISTENCY OF PERMUTATION TESTS 99 3.4 PERMUTATION
CONFIDENCE INTERVAL FOR S 99 3.4.1 PROBLEMS AND EXERCISES 103 3.5
EXTENDING INFERENCE FROM CONDITIONAL TO UNCONDITIONAL 104 3.6 OPTIMAL
PROPERTIES 106 3.6. J PROBLEMS AND EXERCISES 107 3.7 SOME ASYMPTOTIC
PROPERTIES 108 3.7.1 INTRODUCTION 108 3.7.2 TWO BASIC THEOREMS 109 3.8
PERMUTATION CENTRAL LIMIT THEOREMS 111 3.8.1 BASIC NOTIONS 111 3.8.2
PERMUTATION CENTRAL LIMIT THEOREMS 111 3.9 PROBLEMS AND EXERCISES 113
CONTENTS IX 4 THE NONPARAMETRIC COMBINATION METHODOLOGY 117 4.1
INTRODUCTION 117 4.1.1 GENERAL ASPECTS 117 4.1.2 BIBLIOGRAPHIC NATES 118
4.1.3 MAIN ASSUMPTIONSANDNOTATION 120 4.1.4 SOME COMMENTS 121 4.2 THE
NONPARAMETRIC COMBINATION METHODOLOGY 122 4.2.1 ASSUMPTIONS ON PARTIAL
TESTS 122 4.2.2 DESIRABLE PROPERTIES OFCOMBINING FUNCTIONS 123 4.2.3 A
TWO-PHASE ALGORITHMFORNONPARAMETRIC COMBINATION 125 4.2.4 SOME USEFUL
COMBINING FUNCTIONS 128 4.2.5 WHY COMBINATION IS NONPARAMETRIC 134 4.2.6
ON ADMISSIBLE COMBINING FUNCTIONS 135 4.2.7 PROBLEMS AND EXERCISES 135
4.3 CONSISTENCY, UNBIASEDNESS AND POWER OF COMBINED TESTS 137 4.3.1
CONSISTENCY 137 4.3.2 UNBIASEDNESS 137 4.3.3 A NON-CONSISTENT COMBINING
FUNCTION 139 4.3.4 POWER OFCOMBINED TESTS 139 4.3.5 CONDITIONAL
MULTIVARIATE CONFIDENCE REGION FOR S 141 4.3.6 PROBLEMS AND EXERCISES
142 4.4 SOME FURTHER ASYMPTOTIC PROPERTIES 143 4.4.1 GENERAL CONDITIONS
143 4.4.2 ASYMPTOTIC PROPERTIES 143 4.5 FINITE-SAMPLE CONSISTENCY 146
4.5.1 INTRODUCTION 146 4.5.2 FINITE-SAMPLE CONSISTENCY 147 4.5.3 SOME
APPLICATIONS OF FINITE-SAMPLE CONSISTENCY 152 4.6 SOME EXAMPLES OF
NONPARAMETRIC COMBINATION 156 4.6.1 PROBLEMS AND EXERCISES 172 4.7
COMMENTS ON THE NONPARAMETRIC COMBINATION 173 4.7.1 GENERAL COMMENTS 173
4.7.2 FINAL REMARKS 174 5 MULTIPLICITY CONTROL AND CLOSED TESTING 177
5.1 DEFINING RAW AND ADJUSTED P-VALUES 177 5.2 CONTROLLING FOR
MULTIPLICITY 178 5.2.1 MULTIPLE COMPARISON AND MULTIPLE TESTING 178
5.2.2 SOME DEFINITIONS OF THE GLOBAL TYPE I ERROR 179 5.3 MULTIPLE
TESTING 180 5.4 THE CLOSED TESTING APPROACH 181 5.4.1 CLOSED TESTINGFOR
MULTIPLE TESTING 182 5.4.2 CLOSED TESTING USING THE MINP BONFERRONI-HOLM
PROCEDURE 183 5.5 MULT DATA EXAMPLE 186 5.5.1 ANALYSIS USINGMATLAB 186
5.5.2 ANALYSIS USINGR 187 5.6 WASHING TEST DATA 189 5.6.1 ANALYSIS
USINGMATLAB 189 5.6.2 ANALYSIS USINGR 191 5.7 WEIGHTED METHODS FOR
CONTROLLINGFWE AND FDR 193 X CONTENTS 5.8 ADJUSTING STEPWISE P-VALUES
194 5.5.1 SHOWING BIASEDNESS OFSTANDARDP-VALUESFOR STEPWISE REGRESSION
195 5.8.2 ALGORITHM DESCRIPTION 195 5.8.3 OPTIMAL SUBSET PROCEDURES 196
6 ANALYSIS OF MULTIVARIATE CATEGORICAL VARIABLES 197 6.1 INTRODUCTION
197 6.2 THE MULTIVARIATE MCNEMAR TEST 198 6.2.1 AN EXTENSION OF THE
MULTIVARIATEMCNEMAR TEST 200 6.3 MULTIVARIATE GOODNESS-OF-FIT TESTING
FOR ORDERED VARIABLES 201 6.3.1 MULTIVARIATE EXTENSION OFFISHER S EXACT
PROBABILITY TEST 203 6.4 MANOVA WITH NOMINAL CATEGORICAL DATA 203 6.5
STOCHASTIC ORDERING 204 6.5.1 FORMAL DESCRIPTION 204 6.5.2 FURTHER
BREAKING DOWN THE HYPOTHESES 205 6.5.3 PERMUTATION TEST 206 6.6
MULLIFOCUS ANALYSIS 207 6.6.1 GENERAL ASPECTS 207 6.6.2 THE MULTIFOCUS
SOLUTION 208 6.6.3 AN APPLICATION 210 6.7 ISOTONIC INFERENCE 211 6.7.1
INTRODUCTION 211 6.7.2 ALLELICASSOCIATION ANALYSIS IN GENETICS 212 6.7.3
PARAMETRIC SOLUTIONS 213 6.7.4 PERMUTATION APPROACH 214 6.8 TEST ON
MOMENTS FOR ORDERED VARIABLES 215 6.8.1 GENERAL ASPECTS 215 6.8.2 SCORE
TRANSFORMATIONSAND UNIVARIATE TESTS 216 6.8.3 MULTIVARIATE EXTENSION 217
6.9 HETEROGENEITY COMPARISONS 218 6.9.1 INTRODUCTION 218 6.9.2 TESTS FOR
COMPARING HETEROGENEITIES 219 6.9.3 A CASE STUDY IN POPULATION GENETICS
220 6.10 APPLICATION TO PHD PROGRAMME EVALUATION USING SAS 221 6.10.1
DESCRIPTION OF THE PROBLEM 221 6.10.2 GLOBAL SATISFACTION INDEX 222
6.10.3 MULTIVARIATE PERFORMANCE COMPARISONS 224 7 PERMUTATION TESTING
FOR REPEATED MEASUREMENTS 225 7.1 INTRODUCTION 225 7.2 CARRY-OVER
EFFECTS IN REPEATED MEASURES DESIGNS 226 7.3 MODELLING REPEATED
MEASUREMENTS 226 7.3.1 A GENERAL ADDITIVEMODEL 226 7.3.2 HYPOTHESES OF
INTEREST 228 7.4 TESTING SOLUTIONS 228 7.4. J SOLUTIONS USING
THENPCAPPROACH 228 7.4.2 ANALYSIS OFTWO-SAMPLEDOMINANCE PROBLEMS 230
7.4.3 ANALYSIS OF THE CROSS-OVER (AB-BA) DESIGN 230 7.4.4 ANALYSIS OFA
CROSS-OVER DESIGN WITH PAIREDDATA 231 7.5 TESTING FOR REPEATED
MEASUREMENTS WITH MISSING DATA 232 CONTENTS XI 7.6 GENERAL ASPECTS
OFPERMUTATION TESTING WITH MISSING DATA 232 7.6.7 BIBLIOGRAPHIC NOTES
232 7.7 ON MISSING DATA PROCESSES 233 7.7.1 DATA MISSING COMPLETELY AT
RANDOM 233 7.7.2 DATA MISSING NOT AT RANDOM 234 7.8 THE PERMUTATION
APPROACH 234 7.8.1 DELETION, IMPUTATION AND INTENTION TO TREAT
STRATEGIES 235 7.8.2 BREAKING DOWN THE HYPOTHESES 236 7.9 THE STRUCTURE
OF TESTING PROBLEMS 237 7.9.1 HYPOTHESESFORMNAR MODELS 237 7.9.2
HYPOTHESESFORMCAR MODELS 238 7.9.3 PERMUTATION STRUCTURE WITH MISSING
VALUES 239 7.10 PERMUTATION ANALYSIS OF MISSING VALUES 240 7.10.1
PARTITIONING THE PERMUTATION SAMPLE SPACE 240 7.10.2 SOLUTIONFOR
TWO-SAMPLEMCAR PROBLEMS 241 7.10.3 EXTENSIONS TO MULTIVARIATE C-SAMPLE
PROBLEMS 242 7.10.4 EXTENSION TO MNAR MODELS 243 7.11 GERMINA DATA: AN
EXAMPLE OF ANMNAR MODEL 244 7.11.1 PROBLEMDESCRIPTION 245 7.11.2 THE
PERMUTATION SOLUTION 245 7.11.3 ANALYSIS USINGMATLAB 248 7.11.4 ANALYSIS
USING R 248 7.12 MULTIVARIATE PAIRED OBSERVATIONS 251 7.13 REPEATED
MEASURES AND MISSING DATA 252 7.13.1 AN EXAMPLE 253 7.14 BOTULINUM DATA
254 7.14.1 ANALYSIS USING MATLAB 256 7.14.2 ANALYSIS USINGR 258 7.15
WATERFALLS DATA 260 7.15.1 ANALYSIS USING MATLAB 260 7.75.2 ANALYSIS
USING R 264 8 SOME STOCHASTIC ORDERING PROBLEMS 267 8.1 MULTIVARIATE
ORDERED ALTERNATIVES 267 8.2 TESTING FOR UMBRELLA ALTERNATIVES 269 8.2.7
HYPOTHESES AND TESTS IN SIMPLE STOCHASTIC ORDERING 270 8.2.2 PERMUTATION
TESTSFOR UMBRELLA ALTERNATIVES 271 8.3 ANALYSIS OFEXPERIMENTAL TUMOUR
GROWTH CURVES 273 8.4 ANALYSIS OFPERC DATA 276 8.4.1 INTRODUCTION 276
8.4.2 A PERMUTATION SOLUTION 278 8.4.3 ANALYSIS USING MATLAB 279 8.4.4
ANALYSIS USING R 286 9 NPC TESTS FOR SURVIVAL ANALYSIS 289 9.1
INTRODUCTION AND MAIN NOTATION 289 9.7.7 FAILURE TIME DISTRIBUTIONS 289
9.7.2 DATA STRUCTURE 290 9.2 COMPARISON OF SURVIVAL CURVES 291 9.3 AN
OVERVIEW OF THE LITERATURE 292 XII CONTENTS 9.3,1 PERMUTATION TESTS IN
SUNIVAL ANALYSIS 294 9.4 TWO NPC TESTS 295 9.4.1 BREAKING DOWN THE
HYPOTHESES 295 9.4.2 THE TEST STRUCTURE 296 9.4.3 NPC
TESTFORTREATMENT-INDEPENDENT CENSORING 297 9.4.4 NPC
TESTFORTREATMENT-DEPENDENT CENSORING 298 9.5 AN APPLICATION TO A
BIOMEDICAL STUDY 300 10 NPC TESTS IN SHAPE ANALYSIS 303 10.1
INTRODUCTION 303 10.2 A BRIEF OVERVIEW OF STATISTICAL SHAPE ANALYSIS 304
70.2.7 HOW TO DESCRIBE SHAPES 304 70.2.2 MULTIVARIATEMORPHOMETRIES 306
10.3 INFERENCE WITH SHAPE DATA 308 10.4 NPC APPROACH TO SHAPE ANALYSIS
309 70.4.7 NOTATION 309 70,4.2 COMPARATIVE SIMULATION STUDY 311 10.5 NPC
ANALYSIS WITH CORRELATED LANDMARKS 312 10.6 AN APPLICATION TO
MEDITERRANEANMONK SEAL SKULLS 316 10.6.1 THE CASE STUDY 316 70.6.2 SOME
REMARKS 319 70.6.5 SHAPE ANALYSIS USING MATLAB 319 70.6.4 SHAPE ANALYSIS
USING R 321 11 MULTIVARIATE CORRELATION ANALYSIS AND TWO-WAYANOVA 325
11.1 AUTOFLUORESCENCE CASE STUDY 325 77.7.7 A PERMUTATION SOLUTION 326
77.7.2 ANALYSIS USING MATLAB 329 77.7.5 ANALYSIS USING R 329 11.2
CONFOCAL CASE STUDY 333 77.2.7 A PERMUTATION SOLUTION 333 77.2.2
MATLABAND R CODES 335 11.3 TWO-WAY (M)ANOVA 344 77.5.7 BRIEFOVERVIEW
OFPERMUTATION TESTS IN TWO-WAYANOVA 344 77.5.2 MANOVA USINGMATLAB AND R
CODES 346 12 SOME CASE STUDIES USING NPC TEST R10 AND SAS MACROS 351
12.1 AN INTEGRATED APPROACH TO SURVIVAL ANALYSIS IN OBSERVATIONAL
STUDIES 351 72.7.7 A CASE STUDY ON OESOPHAGEAL CANCER 351 72.7.2 A
PERMUTATION SOLUTION 353 72.7.5 SUIVIVAL ANALYSIS WITH STRATIFICATION BY
PROPENSITY SCORE 353 12.2 INTEGRATING PROPENSITY SCORE AND NPC TESTING
354 72.2.7 ANALYSIS USING MATLAB 358 12.3 FURTHER APPLICATIONS WITH NPC
TEST R10 AND SAS MACROS 359 72.5.7 A TWO-SAMPLE EPIDEMIOLOGICAL SURVEY:
PROBLEMDESCRIPTION 359 72.5.2 ANALYSING SETIG DATA USING MATLAB 360
72.5.5 ANALYSING THE SETIG DATA USING R 362 72.5.4 ANALYSING THE SETIG
DATA USING NPC TEST 365 12.3.5 ANALYSIS OFTHE SETIG DATA USING SAS 369
12.4 A COMPARISON OF THREE SURVIVAL CURVES 370 CONTENTS XIII 12.4.1
UNSTRATIFIED SURVIVAL ANALYSIS 371 12.4.2 SURVIVAL ANALYSIS WITH
STRATIFICATION BY PROPENSITY SCORE 371 12.5 SURVIVAL ANALYSIS USING NPC
TEST AND SAS 375 12.5.1 SURVIVALANALYSIS USINGNPC TEST 375 12.5.2
SURVIVALANALYSIS USING SAS 377 12.5.3 SURVIVALANALYSIS USING MATLAB 378
12.6 LOGISTIC REGRESSION AND NPC TEST FOR MULTIVARIATE ANALYSIS 378
72.6./ APPLICATION TO LYMPH NODE METASTASES 378 12.6.2 APPLICATION TO
BLADDER CANCER 380 12.6.3 NPC RESULTS 382 12.6.4 ANALYSIS BY LOGISTIC
REGRESSION 384 12.6.5 SOME COMMENTS 385 REFERENCES 387 INDEX 409
|
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| id | DE-604.BV036432823 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:39:17Z |
| institution | BVB |
| isbn | 0470516410 9780470516416 |
| language | English |
| lccn | 2010000776 |
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| physical | XXI, 417 S. Ill., graph. Darst. |
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| publisher | Wiley |
| record_format | marc |
| series2 | Wiley series in probability and statistics |
| spelling | Pesarin, Fortunato Verfasser aut Permutation tests for complex data theory, applications and software Fortunato Pesarin ; Luigi Salmaso 1. publ. Chichester Wiley 2010 XXI, 417 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Wiley series in probability and statistics Literaturverz. S. [387] - 407 Statistical hypothesis testing Permutations Multivariate analysis Randomisierter Test (DE-588)4294178-7 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 s Randomisierter Test (DE-588)4294178-7 s DE-604 Salmaso, Luigi Verfasser aut GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020305355&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pesarin, Fortunato Salmaso, Luigi Permutation tests for complex data theory, applications and software Statistical hypothesis testing Permutations Multivariate analysis Randomisierter Test (DE-588)4294178-7 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| subject_GND | (DE-588)4294178-7 (DE-588)4040708-1 |
| title | Permutation tests for complex data theory, applications and software |
| title_auth | Permutation tests for complex data theory, applications and software |
| title_exact_search | Permutation tests for complex data theory, applications and software |
| title_full | Permutation tests for complex data theory, applications and software Fortunato Pesarin ; Luigi Salmaso |
| title_fullStr | Permutation tests for complex data theory, applications and software Fortunato Pesarin ; Luigi Salmaso |
| title_full_unstemmed | Permutation tests for complex data theory, applications and software Fortunato Pesarin ; Luigi Salmaso |
| title_short | Permutation tests for complex data |
| title_sort | permutation tests for complex data theory applications and software |
| title_sub | theory, applications and software |
| topic | Statistical hypothesis testing Permutations Multivariate analysis Randomisierter Test (DE-588)4294178-7 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Statistical hypothesis testing Permutations Multivariate analysis Randomisierter Test Multivariate Analyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020305355&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT pesarinfortunato permutationtestsforcomplexdatatheoryapplicationsandsoftware AT salmasoluigi permutationtestsforcomplexdatatheoryapplicationsandsoftware |