Fig. 1

Variable selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model. (A) Tuning parameter (λ) selection in the LASSO model used 10-fold cross-validation with the minimum criteria. The binomial deviance was plotted versus log(λ). Dotted vertical lines were drawn at the optimal values by using the minimum criteria and the 1-standard error of the minimum criteria (the 1-SE criteria). A λ value of 0.012, with log (λ), -4.423 was chosen (1-SE criteria) according to 10-fold cross-validation. (B) LASSO coefficient profiles of the 28 variables. A coefficient profile plot was produced against the log(λ) sequence. A vertical line was drawn at the value selected using 10-fold cross-validation, where optimal λ resulted in 12 nonzero coefficients (except for the intercept)