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Items: 1 to 20 of 160

1.

Reducing bias through directed acyclic graphs.

Shrier I, Platt RW.

BMC Med Res Methodol. 2008 Oct 30;8:70. doi: 10.1186/1471-2288-8-70.

2.

Reducing bias in pelvic floor disorders research: using directed acyclic graphs as an aid.

Sung VW.

Neurourol Urodyn. 2012 Jan;31(1):115-20. doi: 10.1002/nau.21183. Epub 2011 Aug 8.

3.

Graphical presentation of confounding in directed acyclic graphs.

Suttorp MM, Siegerink B, Jager KJ, Zoccali C, Dekker FW.

Nephrol Dial Transplant. 2015 Sep;30(9):1418-23. doi: 10.1093/ndt/gfu325. Epub 2014 Oct 16. Review.

PMID:
25324358
4.

Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology.

Evans D, Chaix B, Lobbedez T, Verger C, Flahault A.

BMC Med Res Methodol. 2012 Oct 11;12:156. doi: 10.1186/1471-2288-12-156.

5.

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
6.

[Causal Inference in Medicine Part II. Directed acyclic graphs--a useful method for confounder selection, categorization of potential biases, and hypothesis specification].

Suzuki E, Komatsu H, Yorifuji T, Yamamoto E, Doi H, Tsuda T.

Nihon Eiseigaku Zasshi. 2009 Sep;64(4):796-805. Japanese.

7.

[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
8.

[Application of directed acyclic graphs in control of confounding].

Xiang R, Dai WJ, Xiong Y, Wu X, Yang YF, Wang L, Dai ZH, Li J, Liu AZ.

Zhonghua Liu Xing Bing Xue Za Zhi. 2016 Jul;37(7):1035-8. doi: 10.3760/cma.j.issn.0254-6450.2016.07.025. Chinese.

PMID:
27453119
9.

Causal inference in cumulative risk assessment: The roles of directed acyclic graphs.

Brewer LE, Wright JM, Rice G, Neas L, Teuschler L.

Environ Int. 2017 May;102:30-41. doi: 10.1016/j.envint.2016.12.005. Epub 2016 Dec 14.

PMID:
27988137
10.

Causal directed acyclic graphs and the direction of unmeasured confounding bias.

VanderWeele TJ, Hernán MA, Robins JM.

Epidemiology. 2008 Sep;19(5):720-8. doi: 10.1097/EDE.0b013e3181810e29.

11.

Directed Acyclic Graphs for Oral Disease Research.

Akinkugbe AA, Sharma S, Ohrbach R, Slade GD, Poole C.

J Dent Res. 2016 Jul;95(8):853-9. doi: 10.1177/0022034516639920. Epub 2016 Mar 21. Review.

12.

"Toward a clearer definition of confounding" revisited with directed acyclic graphs.

Howards PP, Schisterman EF, Poole C, Kaufman JS, Weinberg CR.

Am J Epidemiol. 2012 Sep 15;176(6):506-11. Epub 2012 Aug 17.

13.

Using Directed Acyclic Graphs to detect limitations of traditional regression in longitudinal studies.

Moodie EE, Stephens DA.

Int J Public Health. 2010 Dec;55(6):701-3. doi: 10.1007/s00038-010-0184-x. Epub 2010 Sep 14.

PMID:
20838848
14.

[Causality in objective world: Directed Acyclic Graphs-based structural parsing].

Zheng YJ, Zhao NQ, He YN.

Zhonghua Liu Xing Bing Xue Za Zhi. 2018 Jan 10;39(1):90-93. doi: 10.3760/cma.j.issn.0254-6450.2018.01.019. Chinese.

PMID:
29374904
15.

Causal diagrams for encoding and evaluation of information bias.

Shahar E.

J Eval Clin Pract. 2009 Jun;15(3):436-40. doi: 10.1111/j.1365-2753.2008.01031.x. Epub 2009 Apr 2.

PMID:
19366394
16.

Potential confounding by exposure history and prior outcomes: an example from perinatal epidemiology.

Howards PP, Schisterman EF, Heagerty PJ.

Epidemiology. 2007 Sep;18(5):544-51.

PMID:
17879426
17.

Introduction to causal diagrams for confounder selection.

Williamson EJ, Aitken Z, Lawrie J, Dharmage SC, Burgess JA, Forbes AB.

Respirology. 2014 Apr;19(3):303-11. doi: 10.1111/resp.12238. Epub 2014 Jan 22. Review.

18.

Dependence of confounding on the target population: a modification of causal graphs to account for co-action.

Flanders WD, Johnson CY, Howards PP, Greenland S.

Ann Epidemiol. 2011 Sep;21(9):698-705. doi: 10.1016/j.annepidem.2011.05.002. Epub 2011 Jul 7.

PMID:
21737305
19.

A counterfactual approach to bias and effect modification in terms of response types.

Suzuki E, Mitsuhashi T, Tsuda T, Yamamoto E.

BMC Med Res Methodol. 2013 Jul 31;13:101. doi: 10.1186/1471-2288-13-101.

20.

Robust causal inference using directed acyclic graphs: the R package 'dagitty'.

Textor J, van der Zander B, Gilthorpe MS, Liskiewicz M, Ellison GT.

Int J Epidemiol. 2016 Dec 1;45(6):1887-1894. doi: 10.1093/ije/dyw341.

PMID:
28089956

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