A Comparison of Methods for Analysing Logistic Regression Models with both Clinical and Genomic Variables

Caroline Bazzoli; Sophie Lambert-Lacroix

Conference Poster Year : 2014

A Comparison of Methods for Analysing Logistic Regression Models with both Clinical and Genomic Variables

(1) , (2)

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Caroline Bazzoli

Function : Author

Statistique Apprentissage Machine

Sophie Lambert-Lacroix

Function : Author
PersonId : 857395

Thérapeutique Recombinante Expérimentale

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Applications [stat.AP] Methodology [stat.ME] Other Statistics [stat.ML] Genetics

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Bazzoli_ERCIM_2014.pdf (243.52 Ko)

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Caroline Bazzoli : Connect in order to contact the contributor

https://hal.science/hal-01905592

Submitted on : Thursday, October 25, 2018-9:44:48 PM

Last modification on : Saturday, April 27, 2024-3:14:57 AM

Long-term archiving on: Saturday, January 26, 2019-4:11:20 PM

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hal-01905592 , version 1 (25-10-2018)

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HAL Id : hal-01905592 , version 1

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Caroline Bazzoli, Sophie Lambert-Lacroix. A Comparison of Methods for Analysing Logistic Regression Models with both Clinical and Genomic Variables. ERCIM 2014 - 7th International Conference of the ERCIM Working Group on Computational and Methodological Statistics, Dec 2014, Pise, Italy. ⟨hal-01905592⟩

A Comparison of Methods for Analysing Logistic Regression Models with both Clinical and Genomic Variables

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