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· 분류 : 외국도서 > 과학/수학/생태 > 수학 > 확률과 통계 > 다변량 분석
· ISBN : 9780470286395
· 쪽수 : 376쪽
· 출판일 : 2010-09-07
목차
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
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, 127
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 Specifi cation, 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 Stratifi cation, 200
8.3 Noncompliance, 209
8.4 Attrition, 214
Guidepost 8, 215
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
