What can statistics contribute to a causal understanding?

Scandinavian Journal of Statistics

Volumn 34, Issue 1, 2007, Pages 155-168

  Aalen, Odd O ^a   Frigessi, Arnoldo ^a  

^a UNIVERSITY OF OSLO   (Norway)

Author keywords

Causality; Counterfactual models; Dynamic path analysis; Granger causality; Local dependence; Mechanistic models

Indexed keywords

EID: 33847416508     PISSN: 03036898     EISSN: 14679469     Source Type: Journal    
DOI: 10.1111/j.1467-9469.2006.00549.x     Document Type: Article

References (46)

1. Aalen, O. O. (1978). Nonparametric inference for a family of counting processes. Ann. Statist. 6, 701-726.
2. Aalen, O. O. (1987). Dynamic modelling and causality. Scand. Actuar. J. 177-190.
3. Aalen, O. O., Borgan, N. & Thormann, J. (1980). Interaction between life history events. Non-parametric analysis for prospective and retrospective data in the presence of censoring. Scand. J. Statist. 7, 161-171.
4. Andersen, P. K., Borgan, Ø., Gill, R. D. & Keiding, N. (1993). Statistical models based on counting processes. Springer-Verlag, New York, NY.
5. Bollen, K. A. (1989). Structural equations with latent variables. Wiley, New York, NY.
6. Brovelli, A., Ding, M., Ledberg, A., Chen, Y., Nakamura, R. & Bressler, S. L. (2004). Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. Proc. Natl Acad. Sci. USA 101, 9849-9854.
7. Callow, M. J., Stoltzfus, L. J., Lawn, R. M. & Rubin, E. M. (1994). Expression of human apolipoprotein B and assembly of lipoprotein(a) in transgenic mice. Proc. Natl Acad. Sci. USA 91, 2130-2134.
8. Corrigan, R. & Denton, P. (1996). Causal understanding as a developmental primitive. Dev. Rev. 16, 162-202.
9. Cox, D. R. & Wermuth, N. (2004). Causality: a statistical view. Int. Statist. Rev. 72, 285-305.
10. Didelez, V. (2000). Graphical models for event history analysis based on local independence. Dissertation, University of Dortmund, Dortmund.
11. Didelez, V. (2006). Graphical models for composable finite Markov processes. Scand. J. Statist. doi: 10.1111/j.1467-9469.2006.00528.x.
12. Diggle, P. J., Heagerty, P., Liang, K.-Y. & Zeger, S. L. (2002). Analysis of longitudinal data, 2nd edn. Oxford University Press, Oxford.
13. Editors (2000). Looking back on the millennium in medicine. N. Engl. J. Med. 342, 42-49.
14. Fosen, J., Ferkingstad, E., Borgan, Ø. & Aalen, O. O. (2006). Dynamic path analysis - a new approach to analyzing time-dependent covariates. Lifetime Data Anal. 12, 143-167.
15. Frigessi, A., van de Wiel, M. A., Holden, M., Svendsrud, D. H., Glad, I. K. & Lyng, H. (2005). Genomewide estimation of transcript concentrations from spotted cDNA microarray data. Nucl. Acids Res. 33, e143; doi: 10.1093/nar/gni141.
16. Gilbert, P. B., Bosch, R. J. & Hudgens, M. G. (2003). Sensitivity analysis for the assessment of causal vaccine effects on viral load in HIV clinical trials. Biometrics 59, 531-541.
17. Glazier, A. M., Nadeau, J. H. & Aitman, T. J. (2002). Finding genes that underlie complex traits. Science 298, 2345-2349.
18. Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424-438.
19. Hume, D. (1965). An abstract of a treatise on human nature, 1740. Introduction by J. Keynes and P. Sraffa. Archon Books, Hamden, CT (Original work written in 1740; abstract published in 1938).
20. Kalbfleisch, J. D. & Prentice, R. L. (2002). The statistical analysis of failure time data, 2nd edn. Wiley, Hoboken, NJ.
21. Lauritzen, S. L. (1996). Graphical models. Clarendon, Oxford.
22. Lodygin, D., Epanchintsev, A., Menssen, A., Diebold, J. & Hermeking, H. (2005). Functional epigenomics identifies genes frequently silenced in prostate cancer. Cancer Res. 65, 4218-4227.
23. Machamer, P., Darden, L. & Craver, C. F. (2000). Thinking about mechanisms. Philos. Sci. 67, 1-25.
24. Myers, C. L., Robson, D., Wible, A., Hibbs, M. A., Chiriac, C., Theesfeld, C. L., Dolinski, K. & Troyanskaya, O. G. (2005). Discovery of biological networks from diverse functional genomic data. Genome Biol. 6, R114.
25. Page, G. P., George, V., Go, R. C., Page, P. Z. & Allison, D. B. (2003). "Are we there yet?": deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits. Am. J. Hum. Genet. 73, 711-719.
26. Pearl, J. (2000). Causality: models, reasoning and inference. Cambridge University Press, Cambridge.
27. Pearson, E. R., Starkey, B. J., Powell, R. J., Gribble, F. M., Clark, P. M. & Hattersley, A. T. (2003). Genetic cause of hyperglycaemia and response to treatment in diabetes. Lancet 362, 1275-1281.
28. Penrose, R. (1990). The emperor's new mind. Oxford University Press, Oxford.
29. Preskorn, S. H. (2001). Antipsychotic drug development in the pre-human-genome era: a full circle. J. Psychiatr. Pract. 7, 209-213.
30. Pötter, U. & Blossfeld, H.-P. (2001). Causal inference from series of events. Eur. Sociol. Rev. 17, 21-32.
31. Riordan, J. R., Rommens, J. M., Kerem, B., Alon, N., Rozmahel, R., Grzelczak, Z., Zielenski, J., Lok, S., Plavsic, N., Chou, J. L., Drumm, M. L., Iannuzzi, M. C., Collins, F. S. & Tsui, L.-C. (1989). Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA. Science 245, 1066-1073.
32. Robins, J. M. (1986). A new approach to causal inference in mortality studies with a sustained exposure period - application to control of the healthy worker survivor effect. Math. Model. 7, 1393-1512.
33. Robins, J. M. (1989). The analysis of randomized and non-randomized AIDS treatment trials using a new approach to causal inference in longitudinal studies. In Health service research methodology: a focus on AIDS (eds Sechrest, L., Freeman, H. & Mulley, A.), 113-159. National Center for Health Services Research, US Public Health Service, Rockville, MD.
34. Robins, J. M., Hernan, M. A. & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology 11, 550-560.
35. Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. J. Educ. Psychol. 66, 688-701.
36. Schweder, T. (1970). Composable Markov processes. J. Appl. Probab. 7, 400-410.
37. Serban, N. & Wasserman, L. (2003). Identifying genes altered by a drug in a temporal microarray data: a case study. Available at http://www.isye.gatech.edu/~nserban/jsm.pdf (accessed November 3, 2006).
38. Shen-Orr, S. S., Miko, R., Mangan, S. & Alon, U. (2002). Network motifs in the transcriptional regulation networks of Eschericia coli. Nat. Genet. doi: 10.1038/ng881.
39. Spellman, P. T., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P. O., Botstein, D. & Futcher, B. (1998). Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell 9, 3273-3297.
40. Strogatz, S. H. (2003). Exploring complex networks. Nature 410, 268-276.
41. Suppes, P. (1970). A probabilistic theory of causality. North-Holland, Amsterdam.
42. Tian, L., Greenberg, S. A., Kong, S. W., Altschuler, J., Kohane, I. S. & Park, P. J. (2005). Discovering statistically significant pathways in expression profiling studies. Proc. Natl Acad. Sci. USA 102, 13544-13549.
43. Ulrich, C. M., Nijhout, H. F. & Reed, M. C. (2006). Mathematical modelling: epidemiology meets systems biology. Cancer Epidemiol. Biomarkers Prev. 15, 827-829.
44. Wagner, A. (2002). Estimating coarse gene network structure from large-scale gene perturbation data. Genome Res. 12, 309-315.
45. Wright, S. (1921). Correlation and causation. J. Agric. Res. 20, 557-585.
46. Zeilinger, A. (2005). The message of the quantum. Nature 438, 743.