Inference for additive interaction under exposure misclassification

Biometrika

Volumn 99, Issue 2, 2012, Pages 502-508

  Vanderweele, Tyler J ^a  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Causal inference; Epistasis; Interaction; Misclassification; Sufficient cause; Synergism

Indexed keywords

EID: 84861620969     PISSN: 00063444     EISSN: 14643510     Source Type: Journal    
DOI: 10.1093/biomet/ass012     Document Type: Article

References (23)

1. BROSS, I. (1954). Misclassification in 2 × 2 tables. Biometrics 10, 478-86.
2. CANONICAO, M.,OLIÉ, V., CARCAILLON, L., TUBERT-BITTER, P. & SCARABIN, P.-Y. (2008). Synergism between non- O blood group and oral estrogen in the risk of vennous thromboemolism among postmenopausal women. The ESTHER Study. Thromb. Haemost. 99, 246-8.
3. CHENG, K. F. & LIN, W. J. (2009). The effects of misclassification in studies of gene-environment interactions. Hum. Hered. 67, 77-87.
4. CORDELL, H. J. (2009). Detecting gene-gene interactions that underlie human diseases. Nature Rev. Genet. 10, 392-404.
5. DOSEMECI, M., WACHOLDER, S. & LUBIN, J. H. (1990). Does nondifferential misclassification of exposure always bias a true effect towards the null value? Am. J. Epidemiol. 132, 746-8.
6. GARCIA-CLOSAS, M., THOMPSON, W. D. & ROBINS, J. M. (1998). Differential misclassifications and the assessment of gene-environment interactions. Am. J. Epidemiol. 147, 426-33.
7. GREENLAND, S. & POOLE, C. (1988). Invariants and noninvariants in the concept of interdependent effects. Scand. J. Work Envir. Health 14, 125-9.
8. GREENLAND, S., LASH, T. L. & ROTHMAN K. J. (2008). Concepts of interaction. In Modern Epidemiology, Ed. K. J. Rothman, S. Greenland and T. L. Lash, 3rd ed., pp. 71-83. Philadelphia: Lippincott Williams & Wilkins.
9. HOSMER, D. W. & LEMESHOW, S. (1992). Confidence interval estimation of interaction. Epidemiology 3, 452-6.
10. LINDSTRÖM, S., YEN, Y.- C., SPIEGELMAN, D. & KRAFT, P. (2009). The impact of gene-environment dependence and misclassification in genetic association studies incorporating gene-environment interactions. Hum. Hered. 68, 171-81.
11. RICHARDSON, D. B. & KAUFMAN, J. S. (2009). Estimation of the relative excess risk due to interaction and associated confidence bounds. Am. J. Epidemiol. 169, 756-60.
12. ROTHMAN, K. J. (1976). Causes. Am. J. Epidemiol. 104, 587-92.
13. RUBIN, D. B. (1974). Estimating causal effects of treatments in randomized and non-randomized studies. J. Educ. Psychol. 66, 688-701.
14. VANDERWEELE, T. J. (2009). Sufficient cause interactions and statistical interactions. Epidemiology 20, 6-13.
15. VANDERWEELE, T. J. (2010a). Empirical tests for compositional epistasis. Nature Rev. Genet. 11, 166.
16. VANDERWEELE, T. J. (2010b). Epistatic interactions. Statist. Appl. Genet. Molec. Biol. 9, 1-22.
17. VANDERWEELE, T. J. & KNOL, M. J. (2011). Remarks on antagonism. Am. J. Epidemiol. 173, 1140-7.
18. VANDERWEELE, T. J. & ROBINS J. M. (2007). The identification of synergism in the sufficient-component cause framework. Epidemiology 18, 329-39.
19. VANDERWEELE, T. J. & ROBINS, J. M. (2008). Empirical and counterfactual conditions for sufficient cause interactions. Biometrika 95, 49-61.
20. VANDERWEELE, T. J.,CHEN, Y. & AHSAN, H. (2011). Inference for causal interactions for continuous exposures under dichotomization. Biometrics 67, 1414-21.
21. VANSTEELANDT, S., VANDERWEELE, T. J., TCHETGEN, E. J. & ROBINS, J. M. (2008). Multiply robust inference for statistical interactions. J. Am. Statist. Assoc. 103, 1693-704.
22. VANSTEELANDT, S., VANDERWEELE, T. J. & ROBINS, J. M. (2012). Semiparametric tests for sufficient cause interactions. J. R. Statist. Soc. B 74, 223-44.
23. ZHANG, L.,MUKHERJEE, B.,GHOSH, M.,GRUBER, S. & MORENO, V. (2008). Accounting for error due to misclassification of exposures in case-control studies of gene-environment interaction. Statist. Med. 27, 2756-83.