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Causal analysis in biomedicine and epidemiology : based on minimal sufficient causation / Mikel Aickin.

Holman Biotech Commons R853.S7 A335 2002
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Levy Dental Medicine Library - Stacks R853.S7 A335 2002
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Format:
Book
Author/Creator:
Aickin, Mikel.
Series:
Biostatistics (New York, N.Y.) ; 9.
Biostatistics : a series of references and textbooks ; 9
Language:
English
Subjects (All):
Medicine--Research--Statistical methods.
Medicine.
Epidemiology--Statistical methods.
Epidemiology.
Biometry.
Causation.
Medicine--statistics & numerical data.
Epidemiology--statistics & numerical data.
Medical Subjects:
Medicine--statistics & numerical data.
Epidemiology--statistics & numerical data.
Biometry.
Physical Description:
ix, 224 pages : illustrations ; 24 cm.
Place of Publication:
New York : Marcel Dekker, [2002]
Summary:
Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new method of model parametritization. Illustrates structural equations and graphical elements for complex causal systems.
Contents:
2. What Is Causation? 7
3. Naive Minimal Sufficient Cause 13
4. Events and Probabilities 21
5. Unitary Algebra 31
6. Nontrivial Implication 39
8. The One-Factor Model 49
9. Graphical Elements 59
10. Causations 67
11. Structural Equations 73
12. The Two-Factor Model 77
13. Down Syndrome Example 83
14. Marginalization 87
15. Stratification 91
16. Obesity Example 95
17. Attribution 101
18. Indirect Cause: Probabilities 107
19. Indirect Cause: Structures 113
20. Reversal 117
21. Gestational Diabetes Example 123
22. More Reversal 127
23. Double Reversal 133
24. Complex Indirect Cause 139
25. Dual Causation: Probabilities 143
26. Dual Causation: Structures 147
27. Paradoxical Causation 151
28. Interventions 155
29. Causal Covariance 163
30. Unitary Rates 169
31. Functional Causation 177
32. The Causation Operator 183
33. Causal Modeling 187
34. Dependence 199
35. DAG Theory 205.
Notes:
Includes bibliographical references (pages 219-222) and index.
ISBN:
0824707486
OCLC:
48263750

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