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1.
Simonetto, C. ; Heier, M. ; Peters, A. ; Kaiser, J.C. & Rospleszcz, S.: From atherosclerosis to myocardial infarction - a process-oriented model investigating the role of risk factors. Am. J. Epidemiol. 191, 1766–1775 (2022)
2.
Simonetto, C. ; Heier, M. ; Peters, A. ; Kaiser, J.C. & Rospleszcz, S.: Response to AJE-00301-2022 Invited Commentary "Mechanistic and biologically based models in epidemiology; A powerful underutilized tool" by Rafael Meza & Jihyoun Jeon. Am. J. Epidemiol. 191, 1781–1782 (2022)
3.
Eidemüller, M. ; Holmberg, E.* ; Lundell, M.* & Karlsson, P.*: Evidence for increased susceptibility to breast cancer from exposure to ionizing radiation due to a familial history of breast cancer: Results from the Swedish hemangioma cohort. Am. J. Epidemiol. 190, 76-84 (2021)
4.
Benet, M.* et al.: Integrating clinical and epidemiologic data on allergic diseases across birth cohorts: A harmonization study in the mechanisms of the development of allergy project. Am. J. Epidemiol. 188, 408-417 (2019)
5.
de Vries, P.S.* et al.: Multiancestry genome-wide association study of lipid levels incorporating gene-alcohol interactions. Am. J. Epidemiol. 188, 1033-1054 (2019)
6.
Pesch, B.* et al.: Exposure to welding fumes, hexavalent chromium, or nickel and risk of lung cancer. Am. J. Epidemiol. 188, 1984-1993 (2019)
7.
Yu, B.* et al.: The consortium of metabolomics studies (COMETS): Metabolomics in 47 prospective cohort studies. Am. J. Epidemiol. 188, 991-1012 (2019)
8.
Beyerlein, A. ; Donnachie, E.* & Ziegler, A.-G.: Infections in early Life and development of celiac disease. Am. J. Epidemiol. 186, 1277-1280 (2017)
9.
Paige, E.* et al.: Use of repeated blood pressure and cholesterol measurements to improve cardiovascular disease risk prediction: An individual-participant-data meta-analysis. Am. J. Epidemiol. 186, 899-907 (2017)
10.
Picciotto, S.* ; Peters, A. & Eisen, E.A.*: Hypothetical exposure limits for oil-based metalworking fluids and cardiovascular mortality in a cohort of autoworkers: Structural accelerated failure time models in a public health framework. Am. J. Epidemiol. 181, 563-570 (2015)
11.
Beyerlein, A.: Quantile regression-opportunities and challenges from a user's perspective. Am. J. Epidemiol. 180, 330-331 (2014)
12.
Pennells, L.* et al.: Assessing risk prediction models using individual participant data from multiple studies. Am. J. Epidemiol. 179, 621-632 (2014)
13.
Vlaanderen, J.* et al.: Effect modification of the association of cumulative exposure and cancer risk by intensity of exposure and time since exposure cessation: A flexible method applied to cigarette smoking and lung cancer in the SYNERGY study. Am. J. Epidemiol. 179, 290-298 (2014)
14.
Fernández-Rhodes, L.* et al.: Association of adiposity genetic variants with menarche timing in 92,105 women of European descent. Am. J. Epidemiol. 178, 451-460 (2013)
15.
Kendzia, B.* et al.: Welding and lung cancer in a pooled analysis of case-control studies. Am. J. Epidemiol. 178, 1513-1525 (2013)
16.
Müller, G.* et al.: Regional and neighborhood disparities in the odds of type 2 diabetes: Results from 5 population-based studies in Germany (DIAB-CORE Consortium). Am. J. Epidemiol. 178, 221-230 (2013)
17.
Olsson, A.C.* et al.: Lung cancer risk among hairdressers: A pooled analysis of case-control studies conducted between 1985 and 2010. Am. J. Epidemiol. 178, 1355-1365 (2013)
18.
Brenner, D.R.* et al.: Previous lung diseases and lung cancer risk: A pooled analysis from the International Lung Cancer Consortium. Am. J. Epidemiol. 176, 573-585 (2012)
19.
Salanti, G.* et al.: Underlying genetic models of inheritance in established type 2 diabetes associations. Am. J. Epidemiol. 170, 537-545 (2009)
20.
Heid, I.M. et al.: Estimating the Single Nucleotide Polymorphism Genotype Misclassification From Routine Double Measurements in a Large Epidemiologic Sample. Am. J. Epidemiol. 168, 878-889 (2008)
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