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Items: 1 to 20 of 84

1.

Causal diagrams for epidemiologic research.

Greenland S, Pearl J, Robins JM.

Epidemiology. 1999 Jan;10(1):37-48.

PMID:
9888278
2.

Directed acyclic graphs (DAGs): an aid to assess confounding in dental research.

Merchant AT, Pitiphat W.

Community Dent Oral Epidemiol. 2002 Dec;30(6):399-404.

PMID:
12453109
3.

An overview of relations among causal modelling methods.

Greenland S, Brumback B.

Int J Epidemiol. 2002 Oct;31(5):1030-7. Review.

PMID:
12435780
4.

[Directed acyclic graphs (DAGs) - the application of causal diagrams in epidemiology].

Schipf S, Knüppel S, Hardt J, Stang A.

Gesundheitswesen. 2011 Dec;73(12):888-92. doi: 10.1055/s-0031-1291192. Epub 2011 Dec 22. German.

PMID:
22193898
5.

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
6.
7.
8.

Seeking causal explanations in social epidemiology.

Kaufman JS, Cooper RS.

Am J Epidemiol. 1999 Jul 15;150(2):113-20.

PMID:
10412955
9.

Statistical methods for epidemiologic studies of the health effects of air pollution.

Navidi W, Thomas D, Langholz B, Stram D.

Res Rep Health Eff Inst. 1999 May;(86):1-50; discussion 51-6.

PMID:
10465799
10.

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
11.

Marginal structural models and causal inference in epidemiology.

Robins JM, Hernán MA, Brumback B.

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

PMID:
10955408
12.
13.

Statistical foundations for model-based adjustments.

Greenland S, Pearce N.

Annu Rev Public Health. 2015 Mar 18;36:89-108. doi: 10.1146/annurev-publhealth-031914-122559. Review.

PMID:
25785886
14.

Methodologic implications of the Precautionary Principle: causal criteria.

Weed DL.

Int J Occup Med Environ Health. 2004;17(1):77-81. Review.

PMID:
15212209
15.

Introduction to the use of regression models in epidemiology.

Bender R.

Methods Mol Biol. 2009;471:179-95. doi: 10.1007/978-1-59745-416-2_9.

PMID:
19109780
16.

Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives.

Brookes ST, Whitley E, Peters TJ, Mulheran PA, Egger M, Davey Smith G.

Health Technol Assess. 2001;5(33):1-56. Review.

17.

An application of model-fitting procedures for marginal structural models.

Mortimer KM, Neugebauer R, van der Laan M, Tager IB.

Am J Epidemiol. 2005 Aug 15;162(4):382-8. Epub 2005 Jul 13.

PMID:
16014771
18.

Statistical methods in epidemiology: a comparison of statistical methods to analyze dose-response and trend analysis in epidemiologic studies.

Boucher KM, Slattery ML, Berry TD, Quesenberry C, Anderson K.

J Clin Epidemiol. 1998 Dec;51(12):1223-33.

PMID:
10086814
19.

Mendelian randomization as an instrumental variable approach to causal inference.

Didelez V, Sheehan N.

Stat Methods Med Res. 2007 Aug;16(4):309-30. Review.

PMID:
17715159
20.

[Confounding and causality in epidemiology].

Biggeri A.

Epidemiol Prev. 1999 Oct-Dec;23(4):253-9. Italian.

PMID:
10730465

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