Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Hochschulschrift/Dissertation Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
München
AVM
2009
|
| Schlagwörter: | |
| Links: | http://deposit.dnb.de/cgi-bin/dokserv?id=3262497&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017323388&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | 316 S. graph. Darst. 21 cm |
| ISBN: | 9783899759099 |
Internformat
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| 246 | 1 | 3 | |a Multitrait multimethod multioccasion modeling |
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Datensatz im Suchindex
| _version_ | 1819353193409150976 |
|---|---|
| adam_text | 4 TABLE OF CONTENTS 1 INTRODUCTION.... . . . * .. * 9 1.1 MULTIMETHOD
MEASUREMENT IN PSYCHOLOGY 9 1.2 NEED FOR MTMM LONGITUDINAL MODELS 10 1.3
AVAILABLE MODELS FOR ANALYZING MTMM DATA 10 1.3.1 MTMM MODELS FOR
CROSS-SECTIONAL DATA 10 1.3.1.1 SINGLE INDICATOR MODELS 10 1.3.1.2
MULTIPLE INDICATOR MODELS 16 1.3.2 MTMM MODELS FOR LONGITUDINAL DATA 21
1.3.2.1 THE MULTI-OCCASION CU APPROACH 24 1.3.2.2 THE CS-CM MODEL 26
1.3.2.3 THE MULTI-METHOD LATENT STATE-TRAIT MODEL 27 1.4 AIMS AND
STRUCTUREOF THE PRESENT WORK 30 2 CLASSICAL TEST THEORY AND LATENT STATE
THEORY . ........~ 32 2.1 CLASSICAL TEST THEORY 32 2.2 LATENT STATE
THEORY 37 2.2.1 THE CORRELATED STATE MODEL 38 2.2.2 THE LATENT
DIFFERENCE MODEL 40 2.2.3 THE CS MODEL APPLIED TO MTMM-MO DATA 42 3 THE
CORRELATED STATE-CORRELATED (METHOD-L) MODEL 45 3.1 THE CS-C(M-1) MODEL
45 3.1.1 DEFINITION OF THE CS-C(M-L) MODEL 45 3.1.2 COVARIANCE STRUCTURE
OF THE LATENT VARIABLES 51 3.1.2.1 NON-PERMISSIBLE LATENT CORRELATIONS
51 3.1.2.2 PERMISSIBLE LATENT CORRELATIONS 51 3.1.3 LATENT VARIABLE MEAN
STRUCTURE 57 3.1.4 VARIANCE DECOMPOSITION AND VARIANCE CORAPONENTS 57
3.2 THE CS-C(W-1) MODEL WITH INDICATOR-SPECIFIC FACTORS ACROSS TIME 61
3.2. BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/993315283
DIGITALISIERT DURCH TABLEOF CONTENTS 5 3.2.3.1 NON-PERMISSIBLE LATENT
CORRELATIONS 67 3.2.3.2 PERMISSIBLE LATENT CORRELATIONS 68 3.2.4 LATENT
VARIABLE MEAN STRUCTURE 71 3.2.5 VARIANCE DECOMPOSITION AND VARIANCE
COMPONENTS 72 3.3 MODELING STRATEGIES FOR DIFFERENT FORMS OF
INDICATOR-SPECIFICITY 79 3.4 MEASUREMENT INVARIANCE 80 3.5 FORMAL
DEFINITION OF THE CS-C(M-L) MODELS 81 3.5.1 CS-C(M-L) MODEL WITHOUT
INDICATOR-SPECIFIC FACTORS ACROSS TIME 82 3.5.1.1 MODEL DEFINITION 82
3.5.1.2 EXISTENCE OF COMMON METHOD FACTORS MJU 84 3.5.1.3 ADMISSIBLE
TRANSFORMATIONS AND UNIQUENESS 85 3.5.1.4 MEANINGFULNESS 87 3.5.1.5
COVARIANCE STRUCTURE 89 3.5.1.6 MEAN STRUCTURE 96 3.5.1.7 IDENTIFICATION
97 3.5.2 CS-C(M-L) MODEL WITH INDICATOR-SPECIFIC FACTORS ACROSS TIME 103
3.5.2.1 MODEL DEFINITION 103 3.5.2.2 EXISTENCE OF COMMON
INDICATOR-SPECIFIC FACTORS IS IJT 106 3.5.2.3 ADMISSIBLE TRANSFORMATIONS
AND UNIQUENESS 107 3.5.2.4 MEANINGFULNESS 108 3.5.2.5 COVARIANCE
STRUCTURE 110 3.5.2.6 MEAN STRUCTURE 121 3.5.2.7 IDENTIFICATION 122 3.6
SUMMARY AND DISCUSSION 137 4 THE CS-C(M-1) CHANGE MODEL 139 4.1
INTRODUCING LATENT DIFFERENCE VARIABLES IN THE CS-C(AF-L) MODEL 139 4.2
BASELINE VERSUS NEIGHBOR CHANGE VERSION 143 4.2.1 BASELINE CHANGE
VERSION 143 4.2.2 NEIGHBOR CHANGE VERSION 143 4. TABLE OF CONTENTS 4.4
NON-PERMISSIBLE LATENT CORRELATIONS 146 4.5 PERMISSIBLE LATENT
CORRELATIONS 148 4.6 MEAN STRUCTURE 151 4.7 VARIANCE DECOMPOSITION AND
VARIANCE COMPONENTS 152 4.8 EXTENSIONS OF THE CS-C(AF-L) CHANGE MODEL
155 4.9 SUMMARY AND DISCUSSION 155 APPLICATIONS
........--.*........*.*......*......*.*...*.*.*........**............*.*.**...
................. 162 5.1 DESCRIPTION OF THE DATA SET 162 5.1.1 SAMPLE
162 5.1.2 MEASURES 162 5.2 3-STEP APPROACH TO MODEL TESTING 164 5.2.1
STEP 1: DETERMINATION OF A BASELINE MODEL 167 5.2.2 STEP 2: ASSESSING
INVARIANCE FOR THE REFERENCE METHOD 169 5.2.3 STEP 3: ASSESSING
INVARIANCE FOR THE NON-REFERENCE METHODS 170 5.3 DETAILS ON THE
STATISTICAL ANALYSIS 170 5.3.1 ESTIMATION AND SOFTWARE 170 5.3.2
MULTILEVEL STRUCTURE OF THE DATA 170 5.3.3 HANDLING OF MISSING DATA 171
5.3.4 GOODNESS-OF-FIT ASSESSMENT 171 5.4 APPLICATION OF THE CS-C(M-L)
STATE MODEL 172 5.4.1 ASSESSMENT OF INDICATOR-SPECIFIC EFFECTS 172 5.4.2
ASSESSMENT OF MEASUREMENT INVARIANCE AND MODEL SELECTION 173 5.4.3
CONVERGENT VALIDITY AND VARIANCE COMPONENTS 177 5.4.4 DISCRIMINANT
VALIDITY 186 5.4.5 CONSTRUCT STABILITY AND MEAN CHANGE 186 5.4.6
GENERALIZABILITY AND STABILITY OF METHOD EFFECTS 187 5.5 APPLICATION OF
THE CS-C(M-L) CHANGE MODELS 190 5.5.1 ASSESSMENT OF MEASUREMENT
INVARIANCE AND MODEL SELECTION 190 5.5. 7.1.5 ANALYSIS OF LATENT CHANGE
222 TABLE OF CONTENTS 7 5.5.3 STRUCTURAL MODEL: DISCRIMINANT VALIDITY OF
CHANGE 199 5.5.4 STRUCTURAL MODEL: CORRELATIONS WITH SEX 200 5.6 SUMMARY
AND DISCUSSION OF THE APPLICATIONS 206 6 MONTE CARLO SIMULATION STUDY .
208 6.1 RATIONAL AND AIMS 208 6.2 METHOD 209 6.2.1 POPULATION MODELS 209
6.2.2 CRITERIAFOR EVALUATING THE PERFORMANCE OF THE MODELS 210 6.2.2.1
NON-CONVERGENCE 210 6.2.2.2 IMPROPER SOLUTIONS 210 6.2.2.3 ^TEST 210
6.2.2.4 PARAMETER ESTIMATION BIAS 211 6.2.2.5 STANDARD ERROR BIAS 211
6.2.2.6 COVERAGE 211 6.3 RESULTS 212 6.3.1 CS-C(M-L) STATE MODEL 212
6.3.1.1 NON-CONVERGENCE 212 6.3.1.2 IMPROPER SOLUTIONS 212 6.3.1.3 ^TEST
212 6.3.1.4 PARAMETER BIAS, STANDARD ERROR BIAS, AND COVERAGE 214 6.3.2
CS-C(M-L) CHANGE MODELS 216 6.3.2.1 NON-CONVERGENCE, IMPROPER SOLUTIONS,
AND X 2 TEST 216 6.3.2.2 PARAMETER BIAS, STANDARD ERROR BIAS, AND
COVERAGE 216 6.4 SUMMARY AND RECOMMENDATIONS 216 7 FINAL DISCUSSION »._
_........... *_*..*_* 220 7.1 ADVANTAGES 220 7.1.1 SIMULTANEOUS ANALYSIS
OF MTMM-MO DATA 220 7.1.2 SEPARATION OF VARIANCE COMPONENTS 220 7.1.3
DETERMINATION OF THE DEGREE OF INDICATOR-SPECIFICITY 221 7.1.4
MEASUREMENT INVARIANCE TESTING 221 8 TABLE OF CONTENTS 7.1.6 INCLUSION
OF COVARIATES 222 7.2 LIMITATIONS 223 7.2.1 MODEL COMPLEXITY AND
REQUIRED SAMPLE SIZE 223 7.2.2 TYPES OF INDICATORS 224 7.2.3 REFERENCE
METHOD 224 7.2.4 TYPES OF METHODS 225 7.2.5 MEASUREMENT INVARIANCE 225
7.2.6 DETECTION OF INVARIANCE AND CHANGES IN METHOD EFFECTS 226 7.2.7
INDICATOR-SPECIFIC EFFECTS 227 7.2.8 STATE-TRAIT DISTINCTION 227 7.3
SUMMARY OF GUIDELINES AND TIPS FOR APPLICATIONS 228 7.4 COMPARISON WITH
OTHER APPROACHES 229 7.5 DIRECTIONS FOR FUTURE RESEARCH 230 8
CONCLUSION. . . * ** .... ... . _.* ._ * 232 9 SUMMARY - ~ ~ - -. ***
*.*. 233 10 REFERENCES .. .* . .. . 235 11 LIST OF TABLES 247 12 LIST OF
FIGURES 248 13 APPENDIX 249 13.1 MPLUS SCRIPTS FOR ESTIMATING THE
CS-C(AF-L) MODEL 249 13.1.1 CS-C(M-L) STATE MODEL 249 13.1.2 CS-C(M-L)
BASELINE CHANGE MODEL 258 13.1.3 CS-C(M-L) NEIGHBOR CHANGE MODEL 266
13.2 MPLUS SCRIPTS FOR THE MONTE CARLO SIMULATION STUDY 274 13.2.1
CS-C(M-L) STATE MODEL 274 13.2.2 CS-C(M-L) BASELINE CHANGE MODEL 286
13.2.3 CS-C(M-L) NEIGHBOR CHANGE MODEL 300 14 ZUSAMMENFASSUNG IN
DEUTSCHER SPRACHE ..... 315
|
| any_adam_object | 1 |
| author | Geiser, Christian 1978- |
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| bvnumber | BV035402776 |
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| dewey-full | 150.287 |
| dewey-hundreds | 100 - Philosophy & psychology |
| dewey-ones | 150 - Psychology |
| dewey-raw | 150.287 |
| dewey-search | 150.287 |
| dewey-sort | 3150.287 |
| dewey-tens | 150 - Psychology |
| discipline | Psychologie |
| format | Thesis Book |
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| id | DE-604.BV035402776 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T13:31:42Z |
| institution | BVB |
| isbn | 9783899759099 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017323388 |
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| physical | 316 S. graph. Darst. 21 cm |
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| spellingShingle | Geiser, Christian 1978- Multitrait-multimethod-multioccasion modeling Trait (DE-588)4185857-8 gnd |
| subject_GND | (DE-588)4185857-8 (DE-588)4113937-9 |
| title | Multitrait-multimethod-multioccasion modeling |
| title_alt | Multitrait multimethod multioccasion modeling |
| title_auth | Multitrait-multimethod-multioccasion modeling |
| title_exact_search | Multitrait-multimethod-multioccasion modeling |
| title_full | Multitrait-multimethod-multioccasion modeling Christian Geiser |
| title_fullStr | Multitrait-multimethod-multioccasion modeling Christian Geiser |
| title_full_unstemmed | Multitrait-multimethod-multioccasion modeling Christian Geiser |
| title_short | Multitrait-multimethod-multioccasion modeling |
| title_sort | multitrait multimethod multioccasion modeling |
| topic | Trait (DE-588)4185857-8 gnd |
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