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Dilemmas and Craftsmanship

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Design of Observational Studies

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Abstract

This introductory chapter mentions some of the issues that arise in observational studies and describes a few well designed studies. Section 1.7 outlines the book, describes its structure, and suggests alternative ways to read it.

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Notes

  1. 1.

    She turned into a pillar of salt when she looked where her husband instructed her not to look. Opposed to the story of Lot and his wife is the remark of Immanuel Kant: “Sapere aude” (Dare to know) [29, page 17] . You are, by the way, off to a bad start with these footnotes.

  2. 2.

    An exception is the observation that, with continuous outcomes, the presence of multiple matched controls affects the design sensitivity; see [45] and [47, pp. 222–223].

References

  1. Anderson, I.: Combinatorics of Finite Sets. Oxford University Press, New York (1987)

    Google Scholar 

  2. Angrist, J.D., Krueger, A.B.: Empirical strategies in labor economics. In: Ashenfelter, O., Card, D. (eds.) Handbook of Labor Economics, vol. 3, pp. 1277–1366. Elsevier, New York (1999)

    Google Scholar 

  3. Angrist, J.D., Lavy, V.: Using Maimonides’ rule to estimate the effect of class size on scholastic achievement. Q. J. Econ. 114, 533–575 (1999)

    Google Scholar 

  4. Armstrong, C.S., Kepler, J.D.: Theory, research design assumptions, and causal inferences. J. Account. Econ. 66, 366–373 (2018)

    Google Scholar 

  5. Athey, S., Imbens, G. W.: The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31, 3–32 (2018)

    Google Scholar 

  6. Besley, T., Case, A.: Unnatural experiments? Estimating the incidence of endogenous policies. Econ. J. 110, 672–694 (2000)

    Google Scholar 

  7. Boehnke, M. , Langefeld, C.D.: Genetic association mapping based on discordant sib pairs: the discordant alleles test. Am. J. Hum. Genet. 62, 950–961 (1998)

    Google Scholar 

  8. Bollobás, B.: Combinatorics. Cambridge University Press, New York (1986)

    Google Scholar 

  9. Campbell, D.T. : Factors relevant to the validity of experiments in social settings. Psychol. Bull. 54, 297–312 (1957)

    Google Scholar 

  10. Campbell, D.T.: Methodology and Epistemology for Social Science: Selected Papers. University of Chicago Press, Chicago (1988)

    Google Scholar 

  11. Cochran, W.G.: The planning of observational studies of human populations (with Discussion). J. R. Stat. Soc. Ser. A 128, 234–265 (1965)

    Google Scholar 

  12. Cook, T.D., Shadish, W.R.: Social experiments: some developments over the past fifteen years. Annu. Rev. Psychol. 45, 545–580 (1994)

    Google Scholar 

  13. Cornfield, J. , Haenszel, W. , Hammond, E. , Lilienfeld, A. , Shimkin, M. , Wynder, E. : Smoking and lung cancer: recent evidence and a discussion of some questions. J. Natl. Cancer Inst. 22, 173–203 (1959)

    Google Scholar 

  14. Curtis, D.: Use of siblings as controls in case-control association studies. Ann. Hum. Genet. 61, 319–333 (1997)

    Google Scholar 

  15. Dynarski, S.M.: Does aid matter? Measuring the effect of student aid on college attendance and completion. Am. Econ. Rev. 93, 279–288 (2003)

    Google Scholar 

  16. Evans, L.: The effectiveness of safety belts in preventing fatalities. Accid. Anal. Prev. 18, 229–241 (1986)

    Google Scholar 

  17. Fisher, R.A.: Design of Experiments. Oliver and Boyd, Edinburgh (1935)

    Google Scholar 

  18. Gastwirth, J.L., Krieger, A.M., Rosenbaum, P.R.: Asymptotic separability in sensitivity analysis. J. R. Stat. Soc. Ser. B 62, 545–555 (2000)

    Google Scholar 

  19. Greenstone, M., Gayer, T.: Quasi-experimental and experimental approaches to environmental economics. J. Environ. Econ. Manag. 57, 21–44 (2009)

    Google Scholar 

  20. Greevy, R. , Silber, J.H. , Cnaan, A. , Rosenbaum, P.R.: Randomization inference with imperfect compliance in the ACE-inhibitor after anthracycline randomized trial. J. Am. Stat. Assoc. 99, 7–15 (2004)

    Google Scholar 

  21. Hamermesh, D.S.: The craft of labormetrics. Ind. Labor Relat. Rev. 53, 363–380 (2000)

    Google Scholar 

  22. Heart Protection Study Collaborative Group.: MRC/BHF Heart Protection Study of antioxidant vitamin supplementation in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet 360, 23–33 (2002)

    Google Scholar 

  23. Heckman, J.J.: Micro data, heterogeneity, and the evaluation of public policy: Nobel lecture. J. Polit. Econ. 109, 673–748 (2001)

    Google Scholar 

  24. Hernán, M.A., Alonso, A., Logan, R., Grodstein, F., Michels, K.B., Willett, W.C., Manson, J.E., Robins, J.M.: Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease (with Discussion). Epidemiology 19,766–793 (2008)

    Google Scholar 

  25. Hill, A.B.: The environment and disease: association or causation? Proc. R. Soc. Med. 58, 295–300 (1965)

    Google Scholar 

  26. Holland, P.W.: Statistics and causal inference. J. Am. Stat. Assoc. 81, 945–960 (1986)

    Google Scholar 

  27. Holley, R.: Remarks on the FKG inequalities. Commun. Math. Phys. 36, 227–231 (1974)

    Google Scholar 

  28. Imbens, G.W., Wooldridge, J.M.: Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47, 5–86 (2009)

    Google Scholar 

  29. Kant, I.: What is enlightenment? In: Kant, I. (ed.) Toward Perpetual Peace and Other Writings. Yale University Press, New Haven (1785, 2006)

    Google Scholar 

  30. Katan, M.B.: Apolipoprotein E isoforms, serum cholesterol, and cancer. Lancet 1, 507–508 (1986) Reprinted: Int J Epidemiol 33, 9 (2004)

    Google Scholar 

  31. Katan, M.B.: Commentary: mendelian randomization, 18 years on. Int. J. Epidemiol. 33, 10–11 (2004)

    Article  Google Scholar 

  32. Khaw, K.T., Bingham, S., Welch, A., Luben, R., Wareham, N., Oakes, S., Day, N.: Relation between plasma ascorbic acid and mortality in men and women in EPIC-Norfolk prospective study. Lancet 357, 657–663 (2001)

    Article  Google Scholar 

  33. Laird, N.M., Blacker, D., Wilcox, M.: The sib transmission/disequilibrium test is a Mantel-Haenszel test. Am. J. Hum. Genet. 63, 1915 (1998)

    Google Scholar 

  34. Lawlor, D.A., Smith, G.D., Bruckdorfer, K.R., Kundo, D., Ebrahim, S.: Those confounded vitamins: what can we learn from the differences between observational versus randomized trial evidence? Lancet 363, 1724–1727 (2004)

    Google Scholar 

  35. Meyer, B.D.: Natural and quasi-experiments in economics. J. Bus. Econ. Stat. 13, 151–161 (1995)

    Google Scholar 

  36. Musci, R.J., Stuart, E: Ensuring causal, not casual, inference. Prev. Sci. 20, 452–456 (2019)

    Google Scholar 

  37. Pearce, N., Vandenbroucke, J.P., Lawlor, D.A.: Causal inference in environmental epidemiology: old and new approaches. Epidemiol 30, 311–316 (2019)

    Article  Google Scholar 

  38. Rosenbaum, P.R.: The consequences of adjustment for a concomitant variable that has been affected by the treatment. J. R. Stat. Soc. Ser. A 147, 656–666 (1984)

    Article  Google Scholar 

  39. Rosenbaum, P.R.: On permutation tests for hidden biases in observational studies: an application of Holley’s inequality to the Savage lattice. Ann. Stat. 17, 643–653 (1989)

    Article  MathSciNet  Google Scholar 

  40. Rosenbaum, P.R.: Quantiles in nonrandom samples and observational studies. J. Am. Stat. Assoc. 90, 1424–1431 (1995)

    Article  MathSciNet  Google Scholar 

  41. Rosenbaum, P.R.: Stability in the absence of treatment. J. Am. Stat. Assoc. 96, 210–219 (2001)

    Article  MathSciNet  Google Scholar 

  42. Rosenbaum, P.R.: Observational Studies (2nd ed.). Springer, New York (2002)

    Book  Google Scholar 

  43. Rosenbaum, P.R.: Covariance adjustment in randomized experiments and observational studies. Stat. Sci. 17, 286–327 (2002)

    Article  MathSciNet  Google Scholar 

  44. Rosenbaum, P.R.: Sensitivity analysis for m-estimates, tests, and confidence intervals in matched observational studies. Biometrics 63, 456–464 (2007)

    Article  MathSciNet  Google Scholar 

  45. Rosenbaum, P.R.: Impact of multiple matched controls on design sensitivity in observational studies. Biometrics 69, 118–127 (2013)

    Article  MathSciNet  Google Scholar 

  46. Rosenbaum, P.R.: Two R packages for sensitivity analysis in observational studies. Obs. Stud. 1, 1–17 (2015)

    Google Scholar 

  47. Rosenbaum, P.R.: Observation and Experiment: An Introduction to Causal Inference. Harvard University Press, Cambridge (2017)

    Book  Google Scholar 

  48. Rosenbaum, P.R.: Sensitivity analysis for stratified comparisons in an observational study of the effect of smoking on homocysteine levels. Ann. Appl. Stat. 12, 2312–2334 (2018)

    Article  MathSciNet  Google Scholar 

  49. Rosenzweig, M.R. , Wolpin, K.I.: Natural ‘natural experiments’ in economics. J. Econ. Lit. 38, 827–874 (2000)

    Google Scholar 

  50. Rubin, D.B. : Estimating causal effects of treatments in randomized and nonrandomized studies. J. Educ. Psychol. 66, 688–701 (1974)

    Google Scholar 

  51. Rubin, D.B. : The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat. Med. 26, 20–36 (2007)

    Google Scholar 

  52. Rutter, M.: Identifying the Environmental Causes of Disease: How Do We Decide What to Believe and When to Take Action? Academy of Medical Sciences, London (2007)

    Google Scholar 

  53. Saunders, A.M., Strittmatter, W.J., Schmechel, D., et al.: Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer’s disease. Neurology 43, 1467–1472 (1993)

    Article  Google Scholar 

  54. Savage, I.R.: Contributions to the theory of rank order statistics: applications of lattice theory. Revue de l’Institut Int. de Statistique 32, 52–63 (1964)

    Google Scholar 

  55. Sekhon, J.S.: Opiates for the matches: matching methods for causal inference. Annu. Rev. Polit. Sci. 12, 487–508 (2009)

    Google Scholar 

  56. Sekhon, J.S., Titiunik, R.: When natural experiments are neither natural nor experiments. Am. Polit. Sci. Rev. 106, 35–57 (2012)

    Google Scholar 

  57. Shadish, W.R., Cook, T.D.: The renaissance of field experimentation in evaluating interventions. Annu. Rev. Psychol. 60, 607–629 (2009)

    Google Scholar 

  58. Shadish, W.R., Cook, T.D., Campbell, D.T.: Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton-Mifflin, Boston (2002)

    Google Scholar 

  59. Spielman, R.S., Ewens, W.J.: A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. Am. J. Hum. Genet. 62, 450–458 (1998)

    Google Scholar 

  60. Spielman, R.S., McGinnis, R.E., Ewens, W.J.: Transmission test for linkage disequilibrium. Am. J. Hum. Genet. 52, 506–516 (1993)

    Google Scholar 

  61. Strachan, T., Read, A.P.: Human Molecular Genetics. Garland, New York (2004)

    Google Scholar 

  62. Susser, M.: Epidemiology, Health and Society: Selected Papers. Oxford University Press, New York (1987)

    Google Scholar 

  63. Vandenbroucke, J.P. : When are observational studies as credible as randomized trials? Lancet 363, 1728–1731 (2004)

    Google Scholar 

  64. West, S.G. , Duan, N. , Pequegnat, W. , Gaist, P. , Des Jarlais, D.C. , Holtgrave, D. , Szapocznik, J. , Fishbein, M. , Rapkin, B. , Clatts, M. , Mullen, P.D. : Alternatives to the randomized controlled trial. Am. J. Public Health 98, 1359–1366 (2008)

    Google Scholar 

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  1. Statistics Department, Wharton School, University of Pennsylvania, Philadelphia, PA, USA

    Paul R. Rosenbaum

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R. Rosenbaum, P. (2020). Dilemmas and Craftsmanship. In: Design of Observational Studies. Springer Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-46405-9_1

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