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Items: 1 to 20 of 157

1.

Marginal structural models as a tool for standardization.

Sato T, Matsuyama Y.

Epidemiology. 2003 Nov;14(6):680-6.

PMID:
14569183
2.

Marginal structural models and causal inference in epidemiology.

Robins JM, Hernán MA, Brumback B.

Epidemiology. 2000 Sep;11(5):550-60.

PMID:
10955408
3.

Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

Hernán MA, Brumback B, Robins JM.

Epidemiology. 2000 Sep;11(5):561-70.

PMID:
10955409
4.

Brief Report: Doubly Robust Estimation of Standardized Risk Difference and Ratio in the Exposed Population.

Shinozaki T, Matsuyama Y.

Epidemiology. 2015 Nov;26(6):873-7. doi: 10.1097/EDE.0000000000000363.

PMID:
26275176
5.

Differences between marginal structural models and conventional models in their exposure effect estimates: a systematic review.

Suarez D, Borràs R, Basagaña X.

Epidemiology. 2011 Jul;22(4):586-8. doi: 10.1097/EDE.0b013e31821d0507. Review.

PMID:
21540744
6.

Estimating causal parameters without target populations.

Shahar E.

J Eval Clin Pract. 2007 Oct;13(5):814-6.

PMID:
17824877
7.

Bounds on potential risks and causal risk differences under assumptions about confounding parameters.

Chiba Y, Sato T, Greenland S.

Stat Med. 2007 Dec 10;26(28):5125-35.

PMID:
17525935
8.

Analysis of longitudinal marginal structural models.

Bryan J, Yu Z, Van Der Laan MJ.

Biostatistics. 2004 Jul;5(3):361-80.

PMID:
15208200
9.

Marginal structural models for partial exposure regimes.

Vansteelandt S, Mertens K, Suetens C, Goetghebeur E.

Biostatistics. 2009 Jan;10(1):46-59. doi: 10.1093/biostatistics/kxn012. Epub 2008 May 23.

PMID:
18503036
10.

Marginal structural models might overcome confounding when analyzing multiple treatment effects in observational studies.

Suarez D, Haro JM, Novick D, Ochoa S.

J Clin Epidemiol. 2008 Jun;61(6):525-30. doi: 10.1016/j.jclinepi.2007.11.007. Review.

PMID:
18471655
11.

Bounding causal effects under uncontrolled confounding using counterfactuals.

MacLehose RF, Kaufman S, Kaufman JS, Poole C.

Epidemiology. 2005 Jul;16(4):548-55. Review.

PMID:
15951674
12.

Invited commentary: G-computation--lost in translation?

Vansteelandt S, Keiding N.

Am J Epidemiol. 2011 Apr 1;173(7):739-42. doi: 10.1093/aje/kwq474. Epub 2011 Mar 16.

PMID:
21415028
13.

Use of tamoxifen in pT1a-pT1b, pN0 breast cancer.

Livi L, Saieva C, Paiar F, Simontacchi G, Galardi A, De Luca Cardillo C, Mangoni M, Paoletti L, Ponticelli P, Biti GP.

Eur J Surg Oncol. 2007 Apr;33(3):271-5. Epub 2006 Jul 10.

PMID:
16831531
14.

Acceptance of tamoxifen chemoprevention by physicians and women at risk.

Tchou J, Hou N, Rademaker A, Jordan VC, Morrow M.

Cancer. 2004 May 1;100(9):1800-6.

15.
16.

Marginal structural models: much ado about (almost) nothing.

Shahar E, Shahar DJ.

J Eval Clin Pract. 2013 Feb;19(1):214-22. doi: 10.1111/j.1365-2753.2011.01757.x. Epub 2011 Aug 23.

PMID:
21883715
17.

Nonparametric estimation of the bivariate recurrence time distribution.

Huang CY, Wang MC.

Biometrics. 2005 Jun;61(2):392-402.

PMID:
16011685
18.

Fitting marginal structural models: estimating covariate-treatment associations in the reweighted data set can guide model fitting.

Pullenayegum EM, Lam C, Manlhiot C, Feldman BM.

J Clin Epidemiol. 2008 Sep;61(9):875-81. doi: 10.1016/j.jclinepi.2007.10.024. Epub 2008 May 16.

PMID:
18486447
19.

Marginal structural models for analyzing causal effects of time-dependent treatments: an application in perinatal epidemiology.

Bodnar LM, Davidian M, Siega-Riz AM, Tsiatis AA.

Am J Epidemiol. 2004 May 15;159(10):926-34.

PMID:
15128604
20.

Marginal structural models for the estimation of direct and indirect effects.

VanderWeele TJ.

Epidemiology. 2009 Jan;20(1):18-26. doi: 10.1097/EDE.0b013e31818f69ce. Erratum in: Epidemiology. 2009 Jul;20(4):629.

PMID:
19234398

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