Linear mixed Models in practice: a SAS oriented approach
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Springer
1997
|
| Series: | Lecture notes in statistics
126 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 287 - 299 |
| Physical Description: | XIII, 306 S. graph. Darst. |
| ISBN: | 0387982221 |
Staff View
MARC
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Record in the Search Index
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| adam_text | GEERT VERBEKE GEERT MOLENBERGHS LINEAR MIXED MODELS IN PRACTICE A
SAS-ORIENTED APPROACH SPRINGER CONTENTS PREFACE VII ACKNOWLEDGEMENTS XV
1 INTRODUCTION 1 GEERT MOLENBERGHS, GEERT VERBEKE 2 AN EXAMPLE-BASED
TOUR IN LINEAR MIXED MODELS 11 LUC DUCHATEAU, PAUL JANSSEN 2.1 FIXED
EFFECTS AND RANDOM EFFECTS IN MIXED MODELS 11 2.2 GENERAL LINEAR MIXED
MODELS 22 2.3 VARIANCE COMPONENTS ESTIMATION AND BEST LINEAR UNBIASED
PREDICTION 30 2.3.1 VARIANCE COMPONENTS ESTIMATION 30 2.3.2 BEST LINEAR
UNBIASED PREDICTION (BLUP) 34 2.3.3 EXAMPLES AND THE SAS PROCEDURE MIXED
36 2.4 FIXED EFFECTS: ESTIMATION AND HYPOTHESES TESTING ..;... 39 2.4.1
GENERAL CONSIDERATIONS 39 2.4.2 EXAMPLES AND THE SAS PROCEDURE MIXED 48
2.5 CASE STUDIES 50 2.5.1 CELL PROLIFERATION 50 2.5.2 A CROSS-OVER
EXPERIMENT 54 2.5.3 A MULTICENTER TRIAL 56 3 LINEAR MIXED MODELS FOR
LONGITUDINAL DATA 63 GEERT VERBEKE 3.1 INTRODUCTION 63 X CONTENTS 3.2
THE STUDY OF NATURAL HISTORY OF PROSTATE DISEASE 65 3.3 A TWO-STAGE
ANALYSIS 67 3.4 THE GENERAL LINEAR MIXED-EFFECTS MODEL 70 3.4.1 THE
MODEL 70 3.4.2 MAXIMUM LIKELIHOOD ESTIMATION 72 3.4.3 RESTRICTED MAXIMUM
LIKELIHOOD ESTIMATION . . . . 73 3.4.4 COMPARISON BETWEEN ML AND REML
ESTIMATION . . 74 3.4.5 MODEL-FITTING PROCEDURES 75 3.5 EXAMPLE 76 3.5.1
THE SAS PROGRAM 76 3.5.2 THE SAS OUTPUT 81 3.5.3 ESTIMATION PROBLEMS DUE
TO SMALL VARIANCE COMPONENTS 92 3.6 THE RANDOM AND REPEATED STATEMENTS
94 3.7 TESTING AND ESTIMATING CONTRASTS OF FIXED EFFECTS 96 3.7.1 THE
CONTRAST STATEMENT 96 3.7.2 MODEL REDUCTION 100 3.7.3 THE ESTIMATE
STATEMENT 104 3.8 PROC MIXED VERSUS PROC GLM 106 3.9 TESTS FOR THE NEED
OF RANDOM EFFECTS 108 3.9.1 THE LIKELIHOOD RATIO TEST 109 3.9.2 APPLIED
TO THE PROSTATE DATA 112 3.10 COMPARING NON-NESTED COVARIANCE STRUCTURES
113 3.11 ESTIMATING THE RANDOM EFFECTS 115 3.12 GENERAL GUIDELINES FOR
MODEL CONSTRUCTION 120 3.12.1 SELECTION OF A PRELIMINARY MEAN STRUCTURE
121 3.12.2 SELECTION OF RANDOM-EFFECTS 122 CONTENTS XI 3.12.3 SELECTION
OF RESIDUAL COVARIANCE STRUCTURE 125 3.12.4 MODEL REDUCTION 130 3.13
MODEL CHECKS AND DIAGNOSTIC TOOLS * 132 3.13.1 NORMALITY ASSUMPTION FOR
THE RANDOM EFFECTS * . 133 3.13.2 THE DETECTION OF INFLUENTIAL SUBJECTS
* 144 3.13.3 CHECKING THE COVARIANCE STRUCTURE H * 150 4 CASE STUDIES
155 GEERT VERBEKE, GEERT MOLENBERGHS 4.1 EXAMPLE 1: VARICEAL PRESSURES
155 4.2 EXAMPLE 2: GROWTH CURVES 160 4.3 EXAMPLE 3: BLOOD PRESSURES 167
4.4 EXAMPLE 4: GROWTH DATA 172 4.4.1 MODEL 1 174 4.4.2 MODEL 2 179 4.4.3
MODEL 3 181 4.4.4 GRAPHICAL EXPLORATION 182 4.4.5 MODEL 4 183 4.4.6
MODEL 5 185 4.4.7 MODEL 6 ..... I .. 186 4.4.8 MODEL 7 187 4.4.9 MODEL
8 189 5 LINEAR MIXED MODELS AND MISSING DATA 191 GEERT MOLENBERGHS, LUC
BIJNENS, DAVID SHAW 5.1 INTRODUCTION 191 5.2 MISSING DATA 193 5.2.1
MISSING DATA PATTERNS 194 5.2.2 MISSING DATA MECHANISMS 195 XII CONTENTS
5.2.3 IGNORABILITY 196 5.3 APPROACHES TO INCOMPLETE DATA 197 5.4
COMPLETE CASE ANALYSIS 198 5.4.1 GROWTH DATA 199 5.5 SIMPLE FORMS OF
IMPUTATION 203 5.5.1 LAST OBSERVATION CARRIED FORWARD 204 5.5.2 IMPUTING
UNCONDITIONAL MEANS 209 5.5.3 BUCK S METHOD: CONDITIONAL MEAN IMPUTATION
. . . 214 5.5.4 DISCUSSION OF IMPUTATION TECHNIQUES 218 5.6 AVAILABLE
CASE METHODS 219 5.6.1 GROWTH DATA 220 5.7 LIKELIHOOD-BASED IGNORABLE
ANALYSIS AND PROC MIXED . . 222 5.7.1 GROWTH DATA 223 5.7.2 SUMMARY 233
5.8 HOW IGNORABLE IS MISSING AT RANDOM ? * 233 5.8.1 INFORMATION AND
SAMPLING DISTRIBUTIONS ^ 235 5.8.2 ILLUSTRATION * 237 5.8.3 EXAMPLE *
242 5.8.4 IMPLICATIONS FOR PROC MIXED 243 5.9 THE
EXPECTATION-MAXIMIZATION ALGORITHM ^ 244 5.10 MULTIPLE IMPUTATION * 247
5.10.1 GENERAL THEORY * 248 5.10.2 ILLUSTRATION: GROWTH DATA * 250 5.11
EXPLORING THE MISSING DATA PROCESS 254 5.11.1 GROWTH DATA 255 5.11.2
INFORMATIVE NON-RESPONSE 256 CONTENTS XIII 5.11.3 OSWALD FOR INFORMATIVE
NON-RESPONSE 258 A INFERENCE FOR FIXED EFFECTS 275 A.I ESTIMATION 275
A.2 HYPOTHESIS TESTING 277 A.3 DETERMINATION OF DEGREES OF FREEDOM 277
A.4 SATTERTHWAITE S PROCEDURE 279 B VARIANCE COMPONENTS AND STANDARD
ERRORS 281 C DETAILS ON TABLE 2.10: EXPECTED MEAN SQUARES 283 D EXAMPLE
2.8: CELL PROLIFERATION 285 REFERENCES 287 INDEX 300
|
| any_adam_object | 1 |
| author | Verbeke, Geert Molenberghs, Geert |
| author_facet | Verbeke, Geert Molenberghs, Geert |
| author_role | aut aut |
| author_sort | Verbeke, Geert |
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| building | Verbundindex |
| bvnumber | BV011588759 |
| callnumber-first | Q - Science |
| callnumber-label | QA279 |
| callnumber-raw | QA279.V46 1997 |
| callnumber-search | QA279.V46 1997 |
| callnumber-sort | QA 3279 V46 41997 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SI 856 |
| ctrlnum | (OCoLC)845439720 (DE-599)BVBBV011588759 |
| dewey-full | 519.5/35 519.5/3521 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/35 519.5/35 21 |
| dewey-search | 519.5/35 519.5/35 21 |
| dewey-sort | 3519.5 235 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Book |
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| illustrated | Illustrated |
| indexdate | 2024-07-09T18:12:21Z |
| institution | BVB |
| isbn | 0387982221 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007805357 |
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| physical | XIII, 306 S. graph. Darst. |
| publishDate | 1997 |
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| publisher | Springer |
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| series | Lecture notes in statistics |
| series2 | Lecture notes in statistics |
| spelling | Verbeke, Geert Verfasser aut Linear mixed Models in practice a SAS oriented approach Geert Verbeke ; Geert Molenberghs New York [u.a.] Springer 1997 XIII, 306 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in statistics 126 Literaturverz. S. 287 - 299 SAS (Computer file) Datenverarbeitung Linear models (Statistics) -- Data processing Gemischtes Modell (DE-588)4156565-4 gnd rswk-swf SAS Programm (DE-588)4195685-0 gnd rswk-swf Lineares Modell (DE-588)4134827-8 gnd rswk-swf Lineares Modell (DE-588)4134827-8 s Gemischtes Modell (DE-588)4156565-4 s SAS Programm (DE-588)4195685-0 s DE-604 Molenberghs, Geert Verfasser aut Lecture notes in statistics 126 (DE-604)BV002447846 126 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007805357&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Verbeke, Geert Molenberghs, Geert Linear mixed Models in practice a SAS oriented approach Lecture notes in statistics SAS (Computer file) Datenverarbeitung Linear models (Statistics) -- Data processing Gemischtes Modell (DE-588)4156565-4 gnd SAS Programm (DE-588)4195685-0 gnd Lineares Modell (DE-588)4134827-8 gnd |
| subject_GND | (DE-588)4156565-4 (DE-588)4195685-0 (DE-588)4134827-8 |
| title | Linear mixed Models in practice a SAS oriented approach |
| title_auth | Linear mixed Models in practice a SAS oriented approach |
| title_exact_search | Linear mixed Models in practice a SAS oriented approach |
| title_full | Linear mixed Models in practice a SAS oriented approach Geert Verbeke ; Geert Molenberghs |
| title_fullStr | Linear mixed Models in practice a SAS oriented approach Geert Verbeke ; Geert Molenberghs |
| title_full_unstemmed | Linear mixed Models in practice a SAS oriented approach Geert Verbeke ; Geert Molenberghs |
| title_short | Linear mixed Models in practice |
| title_sort | linear mixed models in practice a sas oriented approach |
| title_sub | a SAS oriented approach |
| topic | SAS (Computer file) Datenverarbeitung Linear models (Statistics) -- Data processing Gemischtes Modell (DE-588)4156565-4 gnd SAS Programm (DE-588)4195685-0 gnd Lineares Modell (DE-588)4134827-8 gnd |
| topic_facet | SAS (Computer file) Datenverarbeitung Linear models (Statistics) -- Data processing Gemischtes Modell SAS Programm Lineares Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007805357&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV002447846 |
| work_keys_str_mv | AT verbekegeert linearmixedmodelsinpracticeasasorientedapproach AT molenberghsgeert linearmixedmodelsinpracticeasasorientedapproach |