Marginal Structural Models for Estimating Effect Modification

Annals of Epidemiology

Volumn 19, Issue 5, 2009, Pages 298-303

  Chiba, Yasutaka ^a   Azuma, Kenichi ^a   Okumura, Jiro ^a  

^a KINKI UNIVERSITY SCHOOL OF MEDICINE   (Japan)

Author keywords

Confounding; Epidemiologic Methods; Gene Environment Interaction; Inverse Probability of Treatment Weighting; Potential Outcomes; Propensity Score

Indexed keywords

ORAL CONTRACEPTIVE AGENT;

ARTICLE; CIGARETTE SMOKING; EPIDEMIOLOGICAL DATA; GENE MUTATION; HUMAN; ISCHEMIC HEART DISEASE; MARGINAL STRUCTURE MODEL; MODEL; ONCOGENE; OVARY CANCER; PRIORITY JOURNAL; REGRESSION ANALYSIS;

CASE-CONTROL STUDIES; COHORT STUDIES; CONFOUNDING FACTORS (EPIDEMIOLOGY); EFFECT MODIFIERS (EPIDEMIOLOGY); FEMALE; HUMANS; LOGISTIC MODELS; MODELS, STATISTICAL; OBSERVATION; PREGNANCY;

EID: 63749123546     PISSN: 10472797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.annepidem.2009.01.025     Document Type: Article

References (25)

1. Merikangas K.R., and Risch N. Genomic priorities and public health. Science 302 (2003) 599-601
2. Hunter D.J. Gene-environment interactions in human diseases. Nat Rev Genet 6 (2005) 287-298
3. Robins J.M. Association, causation, and marginal structural models. Synthese 121 (1999) 151-179
4. Robins J.M. Marginal structural models versus structural nested models as tools for causal inference. In: Halloran M.E., and Berry D. (Eds). Statistical Models in Epidemiology, the Environment and Clinical Trials (1999), Springer-Verlag, New York 95-134
5. Robins J.M., Hernán M.A., and Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology 11 (2000) 550-560
6. Hernán M.A., Brumback B., and Robins J.M. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology 11 (2000) 561-570
7. Hernán M.A., Brumback B., and Robins J.M. Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures. Stat Med 21 (2002) 1689-1709
8. Stürmer T., Joshi M., Glynn R.J., et al. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J Clin Epidemiol 59 (2006) 437-447
9. Breslow N.E., and Day N.E. Statistical Methods in Cancer Research, vol II: The Design and Analysis of Cohort Studies (1987), Oxford University Press, New York
10. Rosenbaum P.R., and Rubin D.B. The central role of the propensity score in observational studies for causal effects. Biometrika 70 (1983) 41-55
11. Joffe M.M., and Rosenbaum P.R. Propensity scores. Am J Epidemiol 150 (1999) 327-333
12. Copas J.B. Randomization models for matched and unmatched 2×2 tables. Biometrika 60 (1973) 267-276
13. Rubin D.B. Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol 66 (1974) 688-701
14. Rothman K.J., Greenland S., and Lash T.L. Modern Epidemiology. 3rd ed. (2008), Lippincott, Philadelphia
15. Pearl J. Causality: Models, Reasoning, and Inference (2000), Cambridge University Press, Cambridge
16. Berk R. Regression Analysis: A Constructive Critique (2003), Sage Publications, Thousand Oaks, CA
17. Hanley J.A., Negassa A., Edwardes M., and Forrester J.E. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol 157 (2003) 364-375
18. Newman S.C. Causal analysis of case-control data. Epidemiol Perspect Innov 3 (2006) 2
19. Månsson R., Joffe M.M., Sun W., and Hennessy S. On the estimation and use of propensity scores in case-control and case-cohort studies. Am J Epidemiol 166 (2007) 332-339
20. Rosenman R.H., Brand R.J., Jenkins C.D., et al. Coronary heart disease in the Western Collaborative Group Study: final follow-up experience of 8 1/2 years. J Am Med Assoc 233 (1975) 872-877
21. Jewell N.P. Statistics for Epidemiology (2003), Chapman and Hall/CRC Press, New York
22. SAS Institute Inc. SAS/STAT® User's Guide: Version 8 Vol 2 (1999), SAS Institute Inc., Cary, NC
23. Modan B., Hartge P., Hirsh-Yechezkel Z., et al. Parity, oral contraceptives and the risk of ovarian cancer among carriers and noncarriers of a BRCA1 or BRCA2 mutation. New Eng J Med 345 (2001) 235-240
24. Chatterjee N., and Carroll R.J. Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies. Biometrika 92 (2005) 399-418
25. Hernán M.A., and Robins J.M. Estimating causal effects from epidemiologic data. J Epidemiol Community Health 60 (2006) 578-586