Думай «почему?». Причина и следствие как ключ к мышлению - Джудиа Перл

Parascandola, M. (2004). Two approaches to etiology: The debate over smoking and lung cancer in the 1950s. Endeavour 28: 81–86. Proctor, R. (2012a). Golden Holocaust: Origins of the Cigarette Catastrophe and the Case for Abolition. University of California Press, Berkeley, CA.

Proctor, R. (2012b). The history of the discovery of the cigarette — lung cancer link: Evidentiary traditions, corporate denial, and global toll. Tobacco Control 21: 87–91.

Salsburg, D. (2002). The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century. Henry Holt and Company, New York, NY.

Stolley, P. (1991). When genius errs: R. A. Fisher and the lung cancer controversy. American Journal of Epidemiology 133: 416–425.

US Department of Health and Human Services (USDHHS). (2014).

The health consequences of smoking–50 years of progress: A report of the surgeon general. USDHHS and Centers for Disease Control and Prevention, Atlanta, GA.

VanderWeele, T. (2014). Commentary: Resolutions of the birthweight paradox: Competing explanations and analytical insights. International Journal of Epidemiology 43: 1368–1373.

Wilcox, A. (2001). On the importance — and the unimportance — of birthweight. International Journal of Epidemiology 30: 1233–1241. Wilcox, A. (2006). The perils of birth weight — A lesson from directed acyclic graphs. American Journal of Epidemiology 164: 1121–1123. Wingo, P. (2003). Long-term trends in cancer mortality in the United States, 1930–1998. Cancer 97: 3133–3275.

Глава 6: Сплошные парадоксы!

Annotated Bibliography

The Monty Hall paradox appears in many introductory books on probability theory (e.g., Grinstead and Snell, 1998, p. 136; Lindley, 2014, p. 201). The equivalent “three prisoners dilemma” was used to demonstrate the inadequacy of non-Bayesian approaches in Pearl (1988, pp. 58–62).

Tierney (July 21, 1991) and Crockett (2015) tell the amazing story of vos Savant’s column on the Monty Hall paradox; Crockett gives several other entertaining and embarrassing comments that vos Savant received from so-called experts. Tierney’s article tells what Monty Hall himself thought of the fuss — an interesting human-interest angle! An extensive account of the history of Simpson’s paradox is given in Pearl (2009, pp. 174–182), including many attempts by statisticians and philosophers to resolve it without invoking causation. A more recent account, geared for educators, is given in Pearl (2014).

Savage (2009), Julious and Mullee (1994), and Appleton, French, and Vanderpump (1996) give the three real-world examples of Simpson’s paradox mentioned in the text (relating to baseball, kidney stones, and smoking, respectively).

Savage’s sure-thing principle (Savage, 1954) is treated in Pearl (2016b), and its corrected causal version is derived in Pearl (2009, pp. 181–182).

Versions of Lord’s paradox (Lord, 1967) are described in Glymour (2006); Hernández-Díaz, Schisterman, and Hernán (2006); Senn (2006); Wainer (1991). A comprehensive analysis can be found in Pearl (2016a).

Paradoxes invoking counterfactuals are not included in this chapter but are no less intriguing. For a sample, see Pearl (2013).

References

Appleton, D., French, J., and Vanderpump, M. (1996). Ignoring a covariate: An example of Simpson’s paradox. American Statistician 50: 340–341.

Crockett, Z. (2015). The time everyone “corrected” the world’s smartest woman. Priceonomics. Available at: http://priceonomics.com/the-time-everyone-corrected-the-worlds-smartest (posted: February 19, 2015).

Glymour, M. M. (2006). Using causal diagrams to understand common problems in social epidemiology. In Methods in Social Epidemiology. John Wiley and Sons, San Francisco, CA, 393–428.

Grinstead, C. M., and Snell, J. L. (1998). Introduction to Probability.

2nd rev. ed. American Mathematical Society, Providence, RI. Hernández-Díaz, S., Schisterman, E., and Hernán, M. (2006). The birth weight “paradox” uncovered? American Journal of Epidemiology 164: 1115–1120.

Julious, S., and Mullee, M. (1994). Confounding and Simpson’s paradox. British Medical Journal 309: 1480–1481.

Lindley, D. V. (2014). Understanding Uncertainty. Rev. ed. John Wiley and Sons, Hoboken, NJ.

Lord, F. M. (1967). A paradox in the interpretation of group comparisons. Psychological Bulletin 68: 304–305.

Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Mateo, CA.

Pearl, J. (2009). Causality: Models, Reasoning, and Inference. 2nd ed. Cambridge University Press, New York, NY.

Pearl, J. (2013). The curse of free-will and paradox of inevitable regret. Journal of Causal Inference 1: 255–257.

Pearl, J. (2014). Understanding Simpson’s paradox. American Statistician 88: 8–13.

Pearl, J. (2016a). Lord’s paradox revisited — (Oh Lord! Kumbaya!). Journal of Causal Inference 4. doi:10.1515/jci-2016-0021.

Pearl, J. (2016b). The sure-thing principle. Journal of Causal Inference 4: 81–86.

Savage, L. (1954). The Foundations of Statistics. John Wiley and Sons, New York, NY.

Savage, S. (2009). The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty. John Wiley and Sons, Hoboken, NJ.

Senn, S. (2006). Change from baseline and analysis of covariance revisited. Statistics in Medicine 25: 4334–4344.

Simon, H. (1954). Spurious correlation: A causal interpretation. Journal of the American Statistical Association 49: 467–479.

Tierney, J. (July 21, 1991). Behind Monty Hall’s doors: Puzzle, debate and answer? New York Times.

Wainer, H. (1991). Adjusting for differential base rates: Lord’s paradox again. Psychological Bulletin 109: 147–151.

Глава 7. За пределами поправок: покорение горы интервенции

Annotated Bibliography

Extensions of the back-door and front-door adjustments were first reported in Tian and Pearl (2002) based on Tian’s c-component factorization. These were followed by Shpitser’s algorithmization of the do-calculus (Shpitser and Pearl, 2006a) and then the completeness results of Shpitser and Pearl (2006b) and Huang and Valtorta (2006).

The economists among our readers should note that the cultural resistance of some economists to graphical tools of analysis (Heckman and Pinto, 2015; Imbens and Rubin, 2015) is not shared by all economists. White and Chalak (2009), for example, have generalized and applied the do-calculus to economic systems involving equilibrium and learning. Recent textbooks in the social and behavioral sciences, Morgan and Winship (2007) and Kline (2016), further signal to young researchers that cultural orthodoxy, like the fear of telescopes in the seventeenth century, is not long lasting in the sciences.

John Snow’s investigation of cholera was very little appreciated during his lifetime, and his one-paragraph obituary in Lancet did not even mention it. Remarkably, the premier British medical journal “corrected” its obituary 155 years later (Hempel, 2013). For more biographical material on Snow, see Hill