Professor of Biostatistics
Vanderbilt University School of Medicine
Abstract
I will explain why statistical inference is distorted by trying different transformations of predictor variables in regression, and show the value of flexibly estimating such transformations with honesty about the number of parameters involved, using regression splines. Then I’ll address the impossible task of empirically selecting the “right” predictor variables for a model, showing examples of (1) failure in a very simple situation, (2) inability to estimate relative predictor importance with precision, and (3) failure of smart selection/shrinkage methods such as lasso to select the right variables with a decent probability.
Bio
Dr. Harrell’s bio can be found here.