Author | Spirtes, Peter. author |
---|---|
Title | Causation, Prediction, and Search [electronic resource] / by Peter Spirtes, Clark Glymour, Richard Scheines |
Imprint | New York, NY : Springer New York, 1993 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-2748-9 |
Descript | XXIV, 530 p. online resource |
1. Introduction and Advertisement -- 1.1 The Issue -- 1.2 Advertisements -- 1.3 Themes -- 2. Formal Preliminaries -- 2.1 Graphs -- 2.2 Probability -- 2.3 Graphs and Probability Distributions -- 2.4 Undirected Independence Graphs -- 2.5 Deterministic and Pseudo-Indeterministic Systems -- 2.6 Background Notes -- 3. Causation and Prediction: Axioms and Explications -- 3.1 Conditionals -- 3.2 Causation -- 3.3 Causality and Probability -- 3.4 The Axioms -- 3.5 Discussion of the Conditions -- 3.6 Bayesian Interpretations -- 3.7 Consequences of The Axioms -- 3.8 Determinism -- 3.9 Background Notes -- 4. Statistical Indistinguishability -- 4.1 Strong Statistical Indistinguishability -- 4.2 Faithful Indistinguishability -- 4.3 Weak Statistical Indistinguishability -- 4.4 Rigid Indistinguishability -- 4.5 The Linear Case -- 4.6 Redefining Variables -- 4.7 Background Notes -- 5. Discovery Algorithms for Causally Sufficient Structures -- 5.1 Discovery Problems -- 5.2 Search Strategies in Statistics -- 5.3 The Wermuth-Lauritzen Algorithm -- 5.4 New Algorithms -- 5.5 Statistical Decisions -- 5.6 Reliability and Probabilities of Error -- 5.7 Estimation -- 5.8 Examples and Applications -- 5.9 Conclusion -- 5.10 Background Notes -- 6. Discovery Algorithms without Causal Sufficiency -- 6.1 Introduction -- 6.2 The PC Algorithm and Latent Variables -- 6.3 Mistakes -- 6.4 Inducing Paths -- 6.5 Inducing Path Graphs -- 6.6 Partially Oriented Inducing Path Graphs -- 6.7 Algorithms for Causal Inference with Latent Common Causes -- 6.8 Theorems on Detectable Causal Influence -- 6.9 Non-Independence Constraints -- 6.10 Generalized Statistical Indistinguishability and Linearity -- 6.11 The Tetrad Representation Theorem -- 6.12 An Example: Math Marks and Causal Interpretation -- 6.13 Background Notes -- 7. Prediction -- 7.1 Introduction -- 7.2 Prediction Problems -- 7.3 Rubin-Holland-Pratt-Schlaifer Theory -- 7.4 Prediction with Causal Sufficiency -- 7.5 Prediction without Causal Sufficiency -- 7.6 Examples -- 7.7 Conclusion -- 7.8 Background Notes -- 8. Regression, Causation and Prediction -- 8.1 When Regression Fails to Measure Influence -- 8.2 A Solution and Its Application -- 8.3 Error Probabilities for Specification Searches -- 8.4 Conclusion -- 9. The Design of Empirical Studies -- 9.1 Observational or Experimental Study? -- 9.2 Selecting Variables -- 9.3 Sampling -- 9.4 Ethical Issues in Experimental Design -- 9.5 An Example: Smoking and Lung Cancer -- 9.6 Appendix -- 10. The Structure of the Unobserved -- 10.1 Introduction -- 10.2 An Outline of the Algorithm -- 10.3 Finding Almost Pure Measurement Models -- 10.4 Facts about the Unobserved Determined by the Observed -- 10.5 Unifying the Pieces -- 10.6 Simulation Tests -- 10.7 Conclusion -- 11. Elaborating Linear Theories with Unmeasured Variables -- 11.1 Introduction -- 11.2 The Procedure -- 11.3 The LISREL and EQS Procedures -- 11.5 Results -- 11.6 Reliability and Informativeness -- 11.7 Using LISREL and EQS as Adjuncts to Search -- 11.8 Limitations of the TETRAD II Elaboration Search -- 11.9 Some Morals for Statistical Search -- 12. Open Problems -- 12.1 Feedback, Reciprocal Causation, and Cyclic Graphs -- 12.2 Indistinguishability Relations -- 12.3 Time series and Granger Causality -- 12.4 Model Specification and Parameter Estimation from the Same Data Base -- 12.5 Conditional Independence Tests -- 13. Proofs of Theorems -- 13.1 Theorem 2.1 -- 13.2 Theorem 3.1 -- 13.3 Theorem 3.2 -- 13.4 Theorem 3.3 -- 13.5 Theorem 3.4 -- 13.6 Theorem 3.5 -- 13.7 Theorem 3.6 (Manipulation Theorem) -- 13.8 Theorem 3.7 -- 13.9 Theorem 4.1 -- 13.10 Theorem 4.2 -- 13.11 Theorem 4.3 -- 13.12 Theorem 4.4 -- 13.13 Theorem 4.5 -- 13.14 Theorem 4.6 -- 13.15 Theorem 5.1 -- 13.16 Theorem 6.1 -- 13.17 Theorem 6.2. -- 13.18 Theorem 6.3 -- 13.19 Theorem 6.4 -- 13.20 Theorem 6.5 -- 13.21 Theorem 6.6 -- 13.22 Theorem 6.7 -- 13.23 Theorem 6.8 -- 13.24 Theorem 6.9 -- 13.25 Theorem 6.10 (Tetrad Representation Theorem) -- 13.26 Theorem 6.11 -- 13.27 Theorem 7.1 -- 13.28 Theorem 7.2 -- 13.29 Theorem 7.3 -- 13.30 Theorem 7.4 -- 13.31 Theorem 7.5 -- 13.32 Theorem 9.1 -- 13.33 Theorem 9.2 -- 13.34 Theorem 10.1 -- 13.35 Theorem 10.2 -- 13.36 Theorem 11.1