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Overview of Topics Related to Model Selection for Regression

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Extended Abstracts Fall 2015

Part of the book series: Trends in Mathematics ((RPCRMB,volume 7))

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We review some strategies proposed in the literature to combine clinical and omics data in a prediction model. We show how these strategies can be performed by using two well-known statistical methods, lasso and boosting, through an application to a biomedical study with a time-to-event outcome.

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Thanks go to Anne-Laure Boulesteix, Carine Legrand, Herbert Braselmann, Julia Hess and Kristian Unger. RDB was supported by grant BO3139/2-2 from the German Research Foundation (DFG).

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Correspondence to Riccardo De Bin .

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De Bin, R. (2017). Overview of Topics Related to Model Selection for Regression. In: Ainsbury, E., Calle, M., Cardis, E., Einbeck, J., Gómez, G., Puig, P. (eds) Extended Abstracts Fall 2015. Trends in Mathematics(), vol 7. Birkhäuser, Cham.

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