An overview of relations among causal modelling methods

International Journal of Epidemiology

Volumn 31, Issue 5, 2002, Pages 1030-1037

  Greenland, Sander ^a   Brumback, Babette ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Bias; Causal diagrams; Causality; Confounding; Data analysis; Direct effects; Epidemiological methods; Graphical models; Inference; Instrumental variables; Risk analysis; Structural equations; Sufficient component cause models

Indexed keywords

EPIDEMIOLOGY;

HYPOTHESIS; INTERMETHOD COMPARISON; MEDICAL RESEARCH; OUTCOMES RESEARCH; POPULATION RESEARCH; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; REVIEW; STATISTICAL MODEL;

EID: 0036816793     PISSN: 03005771     EISSN: None     Source Type: Journal    
DOI: 10.1093/ije/31.5.1030     Document Type: Review

References (41)

1. Spirtes P, Glymour C, Scheines R. Causation, Prediction, and Search. New York: Springer, 1993.
2. Pearl J. Causal diagrams for empirical research (with discussion). Biometrika 1995;82:669-710.
3. Pearl J. Causality. New York: Cambridge, 2000.
4. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology 1999;10:37-48.
5. Robins JM. Data, design, and background knowledge in etiologic inference. Epidemiology 2001;12:313-20.
6. Hernán MA, Hernandez-Diaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation. Am J Epidemiol 2002;155:176-84.
7. Rothman KJ. Causes. Am J Epidemiol 1976;104:587-92.
8. Rothman KJ, Greenland S. Modern Epidemiology. 2nd Edn. Philadelphia: Lippincott, 1998.
9. Little RJ, Rubin DB. Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches. Ann Rev Public Health 2000;21:121-45.
10. Winship C, Morgan SL. Estimation of causal effects from observational data. Ann Rev Sociol 1999;25:659-706.
11. Greenland S. Causal analysis in the health sciences. J Am Statist Assoc 2000;95:286-89.
12. Sobel M. Causal inference in the social sciences. J Am Statist Assoc 2000;95:647-51.
13. Heckman JJ, Vytlacil E. Econometric evaluations of social programs. In: Leamer E, Heckman JJ (eds). Handbook of Econometrics, Vol. 6. New York: Elsevier, 2003 (in press).
14. Kaufman JS, Kaufman S. Assessment of structured socioeconomic effects on health. Epidemiology 2001;12:157-67.
15. Maldonado G, Greenland S. Estimating causal effects (with discussion). Int J Epidemiol 2002;31:421-38.
16. Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect effects. Epidemiology 1992;3:143-55.
17. Cole S, Hernán M. Fallibility in estimating direct effects. Int J Epidemiol 2002;31:163-65.
18. Levin ML. The occurrence of lung cancer in man. Acta Unio Internationalis Contra Cancrum 1953;9:531-41.
19. MacMahon B, Pugh TF. Causes and entities of disease. In: Clark DW, MacMahon B (eds). Preventive Medicine. Boston: Little Brown, 1967, pp. 11-18.
20. Halloran ME, Struchiner CJ. Causal inference for infectious diseases. Epidemiology 1995;6:145-51.
21. Greenland S, Robins JM, Pearl J. Confounding and collapsibility in causal inference. Stat Sci 1999;14:29-46.
22. Greenland S. Ecologic versus individual-level sources of confounding in ecologic estimates of contextual health effects. Int J Epidemiol 2001;30:1343-50.
23. Robins JM. Causal inference from complex longitudinal data. In: Berkane M (ed.). Latent Variable Modeling with Applications to Causality. New York: Springer, 1997, pp. 69-117.
24. Poole C. Positivized epidemiology and the model of sufficient and component causes. Int J Epidemiol 2001;30:707-09.
25. Greenland S, Poole C. Invariants and noninvariants in the concept of interdependent effects. Scand J Work Environ Health 1988;14:125-29.
26. Siemiatycki J, Thomas DC. Biological models and statistical interactions. Int J Epidemiol 1981;10:383-87.
27. Thompson WD. Effect modification and the limits of biological inference from epidemiologic data. J Clin Epidemiol 1991;44:221-32.
28. Beyea J, Greenland S. The importance of specifying the underlying biologic model in estimating the probability of causation. Health Physics 1999;76:269-74.
29. Greenland S, Robins JM. Epidemiology, justice, and the probability of causation. Jurimetrics 2000;40:321-40.
30. Angrist JD, Imbens GW, Rubin DB. Identification of causal effects using instrumental variables (with discussion). J Am Statist Assoc 1996;91:444-72.
31. Bowden RJ, Turkington DA. Instrumental Variables. Cambridge: Cambridge University Press, 1984.
32. Greenland S. An introduction to instrumental variables for epidemiologists. Int J Epidemiol 2000;29:722-29.
33. Bracken M, Belanger K, Hellenbrand K et al. Correlates of residential wiring code used in studies of health effects of residential electromagnetic fields. Am J Epidemiol 1998;148:467-74.
34. Hatch EE, Kleinerman RA, Linet MS et al. Do confounding or selection factors of residential wiring codes and magnetic fields distort findings of electromagnetic field studies? Epidemiology 2000;11:189-98.
35. Holland PW. Statistics and causal inference (with discussion). J Am Statist Assoc 1986;81:945-60.
36. Greenland S. Causality theory for policy uses of epidemiological measures. In: Murray CJL, Mathers C, Salomon J, Lopez AD, Lozano R (eds). Summary Measures of Population Health. Cambridge, MA: Harvard, 2002, Ch. 6.2.
37. Newman SC. Biostatistical Methods in Epidemiology. New York: Wiley, 2001.
38. Witteman J, D'Agostino RB, Stijnen T et al. G-estimation of causal effects: isolated systolic hypertension and cardiovascular death in the Framingham Study. Am J Epidemiol 1998;148:390-401.
39. Joffe MM, Hoover DR, Jacobson LP et al. Estimating the effect of zidovudine on Kaposi's sarcoma from observational data using a rank-preserving structural failure-time model. Stat Med 1998;17: 1073-102.
40. Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effects on zidovudine on the survival of HIV-positive men. Epidemiology 2000;11:561-70.
41. Greenland S, Neutra RR. Control of confounding in the assessment of medical technology. Int J Epidemiol 1980;9:361-67.