Methods of meta-analysis: correcting error and bias in research findings
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New Park, Calif.
Sage
1990
|
| Ausgabe: | 1. print. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. 561 - 576 |
| Beschreibung: | 592 S. |
| ISBN: | 0803932227 0803932235 |
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Datensatz im Suchindex
| _version_ | 1804119497626353667 |
|---|---|
| adam_text | Brief Contents
Preface 13
Acknowledgments 20
Part I. Introduction to Meta Analysis
1: Integrating Research Findings Across Studies 23
2: Study Artifacts and their Impact on Study Outcomes 43
Part II. Meta Analysis of Correlations
3: Meta Analysis of Correlations Corrected Individually
for Artifacts 93
4: Meta Analysis of Correlations Using Artifact
Distributions 158
5: Technical Questions in Meta Analysis of Correlations 199
Part III. Meta Analysis of Experimental Effects and Other
Dichotomous Comparisons
6: Treatment Effects: Experimental Artifacts and Their
Impact 231
7: Meta Analysis Methods for d Values 267
8: Technical Questions in Meta Analysis of d Values 339
Part IV. General Issues in Meta Analysis
9: Second Order Sampling Error and Related Issues 411
10: Cumulation of Findings Within Studies 451
11: Methods of Integrating Findings Across Studies 468
12: Locating, Selecting, and Evaluating Studies 490
13: General Criticisms of Meta Analysis 506
14: Summary of Psychometric Meta Analysis 535
Appendix 541
References 561
Author Index 577
Subject Index 580
About the Authors 592
Contents
Preface 13
Acknowledgments 20
I. Introduction to Meta Analysis
Chapter 1: Integrating Research Findings Across Studies 23
General problem and an example 23
A typical interpretation of the example data 24
Conclusion 26
Critique of the sample review 28
Problems with statistical significance tests 29
The confidence interval 31
Meta analysis 33
Role of meta analysis in the behavioral and social sciences 35
Role of meta analysis in theory development 39
Increasing use of meta analysis 40
Meta analysis in industrial organizational psychology 41
Chapter 2: Study Artifacts and Their Impact on Study
Outcomes 43
Study artifacts 44
Sampling error 44
Error of measurement 44
Dichotomization 46
Range variation in the independent variable 47
Attrition artifacts: Range variation in the dependent variable 49
Imperfect construct validity in the independent variable 52
Imperfect construct validity in the dependent variable 65
Errors in the data 67
Extraneous factors introduced by study procedure 68
Bias in the sample correlation 69
Sampling error, statistical power, and the interpretation of research
literatures 72
An illustration of statistical power 72
A detailed examination of statistical power 75
When and how to cumulate 82
Undercorrection for artifacts in the corrected standard deviation 84
Coding study characteristics and capitalization on chance 85
A look ahead in the book 89
II. Meta Analysis of Correlations
Chapter 3: Meta Analysis of Correlations Corrected
Individually for Artifacts 93
Introduction and overview 93
Bare bones meta analysis: Correcting for sampling error only 100
Estimation of sampling error 100
Correcting the variance for sampling error and an example 102
Moderator variables analyzed by grouping the data and an example 112
Correcting feature correlations for sampling error and an example 115
Artifacts other than sampling error 117
Error of measurement and correction for attenuation 117
Restriction or enhancement of range 125
Dichotomization of independent and dependent variables 133
Imperfect construct validity in independent and dependent variables 138
Attrition artifacts 139
Extraneous factors 140
Bias in the correlation 141
Multiple simultaneous artifacts 142
Meta analysis of individually corrected correlations 143
Individual study computations 144
Combining across studies 146
Final meta analysis estimation 150
Summary of meta analysis correcting each correlation individually 156
Chapter 4: Meta Analysis of Correlations Using Artifact
Distributions 158
Full artifact distribution meta analysis 159
The mean correlation 160
The standard deviation of correlations 163
An example: Error of measurement 173
An example: Unreliability and range restriction 177
An example: Personnel selection with fixed test 179
An example: Personnel selection with varying tests 182
Personnel selection: Findings and formulas in the literature 182
Mixed meta analysis: Partial artifact information in individual studies 187
An example: Dichotomization of both variables 190
Summary of artifact distribution meta analysis of correlations 196
Phase 1 197
Phase 2a: Correcting the mean correlation 197
Phase 2b: Correcting the standard deviation of correlations 197
Chapter 5: Technical Questions in Meta Analysis of
Correlations 199
r versus r1: Which should be used? 199
r versus regression slopes and intercepts in meta analysis 202
Range restriction 202
Measurement error 203
Compatability of units across studies 203
Compatability of findings across meta analysis 203
Intrinsic interpretability 205
Technical factors that cause overestimation of SDp 206
Presence of non Pearson rs 206
Presence of outliers 207
Use of r instead of 7 in the sampling error formula 208
Undercorrection for sampling error variance in the presence of
range restriction 209
Nonlinearity in range correction 209
Other factors causing overestimation of SDp 211
Criticisms of meta analysis procedures for correlations 212
Does meta analysis assume SDp = 0? 213
Bias in r and use of Fisher s z 213
Erroneous use of confidence intervals 218
Is sampling error variance inaccurately estimated? 220
Errors in the Kemery et al. (1987) study 222
Are estimates of SDp unreliable ? 223
Overestimation of variance due to artifacts 224
Alleged problems with the sampling error variance model 226
III. Meta Analysis of Experimental Effects and Other
Dichotomous Comparisons
Chapter 6: Treatment Effects: Experimental Artifacts
and Their Impact 231
Quantification of the treatment effect: The d statistic and the
point biserial correlation 232
Sampling error in d values: Illustrations 236
Case 1: N = 30 236
Case 2:N=68 239
Case 3: #= 400 240
Error of measurement in the dependent variable 241
Error of measurement in the treatment variable 247
Variation across studies in treatment strength 252
Range variation on the dependent variable 253
Dichotomization of the dependent variable 255
Imperfect construct validity in the dependent variable 257
Imperfect construct validity in the treatment variable 260
Bias in the effect size 260
Recording, computational, and transcriptional errors 262
Multiple artifacts and corrections 263
Chapter 7: Meta Analysis Methods for d Values 267
Effect size indices: d and r 268
Maximum value of point biserial r 269
The effect size 271
Correction of the point biserial for unequal sample sizes 274
Examples of the convertibility of r and d 275
Problems of artificial dichotomization 276
An alternative to d: Glass d 276
Meta analysis formulas for Se and 5c 278
Sampling error in the d statistic 281
The standard error for d 281
The confidence interval for d 283
Cumulation and correction of the variance for sampling error 284
Bare bones meta analysis 285
A numerical example 287
Another example: Leadership training by experts 290
Analysis of moderator variables 292
Using study domain subsets 293
Using study characteristic correlations 293
An example: Training by experts versus by managers 295
Another example: Amount of training 299
The correlational moderator analysis 302
Correcting d value statistics for measurement error in the dependent
variable 303
Meta analysis oid values corrected individually and an example 306
Artifact distribution meta analysis and an example 311
Measurement error in the dependent variable in experiments 316
Other artifacts and their effects 319
Correcting for multiple artifacts 321
Attenuation effect of multiple artifacts and correction for the same 321
Disattenuation and sampling error: The confidence interval 324
A formula for meta analysis with multiple artifacts 325
Summary of meta analysis of d values 336
Chapter 8: Technical Questions in Meta Analysis of
d Values 339
Within subjects experimental designs 339
The potentially perfect power of the pre post design 341
The deficiencies of the between subjects design 343
Error of measurement and the within subjects design 348
The treatment by subject interaction 354
Sampling error 364
Meta analysis and the within subjects design 382
The d statistic 382
The treatment by subjects interaction 383
Statistical power in the two designs 388
Designs matched for number of subjects 389
Designs matched for number of measurements or scores 393
Threats to internal and external validity 397
History 399
Maturation 399
Testing 400
Instrumentation 401
Regression to the mean 401
Reactive arrangements 402
Interaction between testing and treatment 403
Interaction between selection and treatment 403
Bias in observed d values 404
Random versus fixed effects models 405
Use of multiple regression in moderator analysis 408
IV. General Issues in Meta Analysis
Chapter 9: Second Order Sampling Error and Related Issues 411
Second order sampling error: General principles 411
Statistical power to detect moderators in meta analysis:
General principles 414
Second order meta analyses 421
Second order sampling error: Technical treatment 422
The homogeneous case 426
The heterogeneous case 428
The detection of moderator variables: Technical treatment 436
The theoretically predicted moderator 437
The unsuspected moderator 440
Comparison of statistical power 447
Chapter 10: Cumulation of Findings Within Studies 451
Fully replicated designs 451
Conceptual replication 451
Conceptual replication and confirmatory factor analysis 454
Conceptual replication: An alternative approach 457
Analysis of subgroups 463
Subgroups and loss of power 463
Subgroups and capitalization on chance 464
Subgroups and suppression of data 465
Subgroups and the bias of disaggregation 465
Conclusion: Use total group correlations 466
Summary 466
Chapter 11: Methods of Integrating Findings Across Studies 468
The traditional narrative procedure 468
The traditional voting method 469
Cumulation of p values across studies 471
Statistically correct vote counting methods 472
Vote counting methods yielding only significance levels 473
Vote counting methods yielding estimates of effect sizes 474
Counting positive significant findings 474
Counting positive results 476
Counting positive and negative significant results 477
Meta analysis of research studies 478
Glassian meta analysis methods 479
Study effects meta analysis 482
Homogeneity test based meta analysis 483
Schmidt Hunter meta analysis methods: Validity generalization 484
Psychometric meta analysis 485
Summary 487
Chapter 12: Locating, Selecting, and Evaluating Studies 490
Conducting a thorough literature search 490
Indices 490
Bibliographies and personal queries 494
Complexities of the search for studies 494
What to do about studies with methodological weaknesses 495
What to report in the review 498
Information needed in reports of primary studies 499
Correlational studies 500
Experimental studies 501
Studies using multiple regression 502
Studies using factor analysis 503
Studies using canonical correlation 504
Studies using MANOVA 504
General comments on reporting in primary studies 505
Chapter 13: General Criticisms of Meta Analysis 506
Availability bias 506
Does source bias exist? 507
Effects of methodological quality on mean effect sizes from
different sources 509
Statistical methods for handling availability bias 510
Rejection of the entire social science research base 515
Mixing of apples and oranges 516
The logical argument 517
The methodological argument 518
Homogeneity 520
Sampling error 521
Real apples and oranges 521
False defense of the narrative review 527
Checklists of rules for meta analysis 532
Criticisms of corrections for attenuation 533
Chapter 14: Summary of Psychometric Meta Analysis 535
Appendix: Meta analysis computer programs for the PC 541
Meta analysis correcting correlations individually 543
Artifact distribution meta analysis of correlations 548
Meta analysis correcting d values individually 553
Artifact distribution meta analysis of d values 556
Program to create data files 559
References 561
Author Index 577
Subject Index 580
About the Authors 592
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| id | DE-604.BV005295377 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T16:27:07Z |
| institution | BVB |
| isbn | 0803932227 0803932235 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-003306478 |
| oclc_num | 20172005 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-739 DE-29 DE-N2 DE-11 DE-12 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-384 DE-703 DE-355 DE-BY-UBR DE-20 DE-824 DE-706 DE-83 DE-188 |
| owner_facet | DE-473 DE-BY-UBG DE-739 DE-29 DE-N2 DE-11 DE-12 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-384 DE-703 DE-355 DE-BY-UBR DE-20 DE-824 DE-706 DE-83 DE-188 |
| physical | 592 S. |
| publishDate | 1990 |
| publishDateSearch | 1990 |
| publishDateSort | 1990 |
| publisher | Sage |
| record_format | marc |
| spelling | Hunter, John Edward 1939-2002 Verfasser (DE-588)131404873 aut Methods of meta-analysis correcting error and bias in research findings John E. Hunter ; Frank L. Schmidt 1. print. New Park, Calif. Sage 1990 592 S. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 561 - 576 Ciencias humanas e sociais larpcal Meta-analyse gtt Méta-analyse Méta-analyse ram Sciences sociales - Méthodes statistiques Sciences sociales - Méthodes statistiques ram Sozialwissenschaften Statistik Meta-Analysis Meta-analysis Research methods Social sciences Statistical methods Statistics Methode (DE-588)4038971-6 gnd rswk-swf Psychologie (DE-588)4047704-6 gnd rswk-swf Forschungsmethode (DE-588)4155046-8 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Metaanalyse (DE-588)4169552-5 gnd rswk-swf Metaanalyse (DE-588)4169552-5 s Methode (DE-588)4038971-6 s Statistik (DE-588)4056995-0 s Psychologie (DE-588)4047704-6 s 1\p DE-604 Forschungsmethode (DE-588)4155046-8 s 2\p DE-604 Schmidt, Frank L. 1944- Verfasser (DE-588)131405470 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003306478&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Hunter, John Edward 1939-2002 Schmidt, Frank L. 1944- Methods of meta-analysis correcting error and bias in research findings Ciencias humanas e sociais larpcal Meta-analyse gtt Méta-analyse Méta-analyse ram Sciences sociales - Méthodes statistiques Sciences sociales - Méthodes statistiques ram Sozialwissenschaften Statistik Meta-Analysis Meta-analysis Research methods Social sciences Statistical methods Statistics Methode (DE-588)4038971-6 gnd Psychologie (DE-588)4047704-6 gnd Forschungsmethode (DE-588)4155046-8 gnd Statistik (DE-588)4056995-0 gnd Metaanalyse (DE-588)4169552-5 gnd |
| subject_GND | (DE-588)4038971-6 (DE-588)4047704-6 (DE-588)4155046-8 (DE-588)4056995-0 (DE-588)4169552-5 |
| title | Methods of meta-analysis correcting error and bias in research findings |
| title_auth | Methods of meta-analysis correcting error and bias in research findings |
| title_exact_search | Methods of meta-analysis correcting error and bias in research findings |
| title_full | Methods of meta-analysis correcting error and bias in research findings John E. Hunter ; Frank L. Schmidt |
| title_fullStr | Methods of meta-analysis correcting error and bias in research findings John E. Hunter ; Frank L. Schmidt |
| title_full_unstemmed | Methods of meta-analysis correcting error and bias in research findings John E. Hunter ; Frank L. Schmidt |
| title_short | Methods of meta-analysis |
| title_sort | methods of meta analysis correcting error and bias in research findings |
| title_sub | correcting error and bias in research findings |
| topic | Ciencias humanas e sociais larpcal Meta-analyse gtt Méta-analyse Méta-analyse ram Sciences sociales - Méthodes statistiques Sciences sociales - Méthodes statistiques ram Sozialwissenschaften Statistik Meta-Analysis Meta-analysis Research methods Social sciences Statistical methods Statistics Methode (DE-588)4038971-6 gnd Psychologie (DE-588)4047704-6 gnd Forschungsmethode (DE-588)4155046-8 gnd Statistik (DE-588)4056995-0 gnd Metaanalyse (DE-588)4169552-5 gnd |
| topic_facet | Ciencias humanas e sociais Meta-analyse Méta-analyse Sciences sociales - Méthodes statistiques Sozialwissenschaften Statistik Meta-Analysis Meta-analysis Research methods Social sciences Statistical methods Statistics Methode Psychologie Forschungsmethode Metaanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003306478&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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