Measurement Error in Lasso: Impact and Likelihood Bias Correction
This paper analyzes the impact of covariate measurement error in the lasso method for penalized regression. First, we present a result showing how the classical result for variable selection consistency breaks down in the presence of measurement error, and then we study a correction method and show how it recovers the consistent variable selection property. Finally, we consider an extension to logistic and Poisson regression. Published in Statistica Sinica.