Bias and causation: models and judgment for valid comparisons
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2010
|
| Schriftenreihe: | Wiley series in probability and statistics
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XV, 348 S. graph. Darst. 24 cm |
| ISBN: | 9780470286395 0470286393 |
Internformat
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| 245 | 1 | 0 | |a Bias and causation |b models and judgment for valid comparisons |c Herbert I. Weisberg |
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| 300 | |a XV, 348 S. |b graph. Darst. |c 24 cm | ||
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| 650 | 0 | 7 | |a Kausalität |0 (DE-588)4030102-3 |2 gnd |9 rswk-swf |
| 653 | |a Discriminant analysis | ||
| 653 | |a Paired comparisons (Statistics) | ||
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Datensatz im Suchindex
| _version_ | 1804148579295559680 |
|---|---|
| adam_text | Titel: Bias and causation
Autor: Weisberg, Herbert I.
Jahr: 2010
Contents
Preface xi
1. What Is Bias? 1
1.1 Apples and Oranges, 2
1.2 Statistics vs. Causation, 3
1.3 Bias in the Real World, 6
Guidepost 1, 23
2. Causality and Comparative Studies 24
2.1 Bias and Causation, 24
2.2 Causality and Counterfactuals, 26
2.3 Why Counterfactuals? 32
2.4 Causal Effects, 33
2.5 Empirical Effects, 38
Guidepost 2, 46
3. Estimating Causal Effects 47
3.1 External Validity, 48
3.2 Measures of Empirical Effects. 50
3.3 Difference of Means. 52
3.4 Risk Difference and Risk Ratio, 55
3.5 Potential Outcomes. 57
3.6 Time-Dependent Outcomes, 60
3.7 Intermediate Variables, 63
3.8 Measurement of Exposure, 64
3.9 Measurement of the Outcome Value, 68
3.10 Confounding Bias, 70
Guidepost 3, 71
vii
VÜi CONTENTS
4. Varieties of Bias 72
4.1 Research Designs and Bias, 73
4.2 Bias in Biomedical Research, 81
4.3 Bias in Social Science Research, 85
4.4 Sources of Bias: A Proposed Taxonomy, 90
Guidepost 4, 92
5. Selection Bias 93
5.1 Selection Processes and Bias, 93
5.2 Traditional Selection Model: Dichotomous Outcome, 100
5.3 Causal Selection Model: Dichotomous Outcome, 102
5.4 Randomized Experiments, 104
5.5 Observational Cohort Studies, 108
5.6 Traditional Selection Model: Numerical Outcome, 111
5.7 Causal Selection Model: Numerical Outcome, 114
Guidepost 5, 121
Appendix, 122
6. Confounding: An Enigma? 126
6.1 What is the Real Problem? 127
6.2 Confounding and Extraneous Causes, 128
6.3 Confounding and Statistical Control, 131
6.4 Confounding and Comparability, 137
6.5 Confounding and the Assignment Mechanism, 139
6.6 Confounding and Model Specification, 141
Guidepost 6, 144
7. Confounding: Essence, Correction, and Detection 145
7.1 Essence: The Nature of Confounding, 146
7.2 Correction: Statistical Control for Confounding, 172
7.3 Detection: Adequacy of Statistical Adjustment, 180
Guidepost 7, 191
Appendix, 192
8. Intermediate Causal Factors 195
8.1 Direct and Indirect Effects, 195
8.2 Principal Stratification, 200
8.3 Noncompliance, 209
CONTENTS IX
8.4 Attrition, 214
Guidepost 8, 216
9. Information Bias 217
9.1 Basic Concepts, 218
9.2 Classical Measurement Model: Dichotomous
Outcome, 223
9.3 Causal Measurement Model: Dichotomous
Outcome, 230
9.4 Classical Measurement Model: Numerical
Outcome, 239
9.5 Causal Measurement Model: Numerical
Outcome, 242
9.6 Covariates Measured with Error, 246
Guidepost 9, 250
10. Sources of Bias 252
10.1 Sampling, 254
10.2 Assignment, 260
10.3 Adherence, 266
10.4 Exposure Ascertainment, 269
10.5 Outcome Measurement, 273
Guidepost 10, 277
11. Contending with Bias 279
11.1 Conventional Solutions, 280
11.2 Standard Statistical Paradigm, 286
11.3 Toward a Broader Perspective, 288
11.4 Real-World Bias Revisited, 293
11.5 Statistics and Causation, 303
Glossary 309
Bibliography 321
Index 340
|
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| illustrated | Illustrated |
| indexdate | 2024-07-10T00:09:23Z |
| institution | BVB |
| isbn | 9780470286395 0470286393 |
| language | English |
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| oclc_num | 699834240 |
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| owner_facet | DE-19 DE-BY-UBM DE-824 |
| physical | XV, 348 S. graph. Darst. 24 cm |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Wiley |
| record_format | marc |
| series2 | Wiley series in probability and statistics |
| spelling | Weisberg, Herbert I. 1944- Verfasser (DE-588)143043315 aut Bias and causation models and judgment for valid comparisons Herbert I. Weisberg Hoboken, NJ Wiley 2010 XV, 348 S. graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Wiley series in probability and statistics Includes bibliographical references and index Bias (DE-588)4133271-4 gnd rswk-swf Kausalität (DE-588)4030102-3 gnd rswk-swf Discriminant analysis Paired comparisons (Statistics) Bias (DE-588)4133271-4 s SWB Kausalität (DE-588)4030102-3 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024553034&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Weisberg, Herbert I. 1944- Bias and causation models and judgment for valid comparisons Bias (DE-588)4133271-4 gnd Kausalität (DE-588)4030102-3 gnd |
| subject_GND | (DE-588)4133271-4 (DE-588)4030102-3 |
| title | Bias and causation models and judgment for valid comparisons |
| title_auth | Bias and causation models and judgment for valid comparisons |
| title_exact_search | Bias and causation models and judgment for valid comparisons |
| title_full | Bias and causation models and judgment for valid comparisons Herbert I. Weisberg |
| title_fullStr | Bias and causation models and judgment for valid comparisons Herbert I. Weisberg |
| title_full_unstemmed | Bias and causation models and judgment for valid comparisons Herbert I. Weisberg |
| title_short | Bias and causation |
| title_sort | bias and causation models and judgment for valid comparisons |
| title_sub | models and judgment for valid comparisons |
| topic | Bias (DE-588)4133271-4 gnd Kausalität (DE-588)4030102-3 gnd |
| topic_facet | Bias Kausalität |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024553034&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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