Partial Variable Selection and its Applications in Biostatistics

Abstract

We propose and study a method for partial covariates selection, which only select the covariates with values fall in their effective ranges. The coefficients estimates based on the resulting data is more interpretable based on the effective covariates. This is in contrast to the existing method of variable selection, in which some variables are selected/deleted in whole. To test the validity of the partial variable selection, we extended the Wilks theorem to handle this case. Simulation studies are conducted to evaluate the performance of the proposed method, and it is applied to a real data analysis as illustration.