Improved Semiparametric Analysis of Polygenic Gene–Environment Interactions in Case–Control Studies
Author:
Funder
National Cancer Institute
Publisher
Springer Science and Business Media LLC
Subject
Biochemistry, Genetics and Molecular Biology (miscellaneous),Statistics and Probability
Link
https://link.springer.com/content/pdf/10.1007/s12561-020-09298-9.pdf
Reference34 articles.
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2. Anderson WF, Matsuno RK, Sherman ME, Lissowska J, Gail MH, Brinton LA, Yang XR, Peplonska B, Chen BE, Rosenberg PS, Chatterjee N, Szeszenia-Dabrowska N, Bardin-Mikolajczak A, Zatonski W, Devesa SS, García-Closas M (2007) Estimating age-specific breast cancer risks: a descriptive tool to identify age interactions. Cancer Causes Control 18:439–447
3. Breslow NE, Robins JM, Wellner JA (2000) On the semi-parametric efficiency of logistic regression under case–control sampling. Bernoulli 6:447–55
4. Canzian F, Cox DG, Setiawan VW, Stram DO, Ziegler RG, Dossus L, Beckmann L, Blanché H, Barricarte A, Berg CD et al (2010) Comprehensive analysis of common genetic variation in 61 genes related to steroid hormone and insulin-like growth factor-i metabolism and breast cancer risk in the NCI breast and prostate cancer cohort consortium. Hum Mol Genet 19:3873–3884
5. Chatterjee N, Carroll RJ (2005) Semiparametric maximum likelihood estimation in case–control studies of gene–environment interactions. Biometrika 92:399–418
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