Statistical predictions with glmnet
Solveig EngebretsenOslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, University of Oslo, Oslo, NorwayJon BohlinDivision for Infection Control and Environmental Health, Department of Infectious Disease Epidemiology and Modelling, Norwegian Institute of Public Health, Oslo, Norway
2019en
ABI
Annotatsiya
Elastic net type regression methods have become very popular for prediction of certain outcomes in epigenome-wide association studies (EWAS). The methods considered accept biased coefficient estimates in return for lower variance thus obtaining improved prediction accuracy. We provide guidelines on how to obtain parsimonious models with low mean squared error and include easy to follow walk-through examples for each step in R.
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