I am trying to quantify the proportion of total predictive information contributed by each predictor in a model with a binary outcome fit in a large sample. I’m reading page 206 in Regression Modelling Strategies covering this topic.
The helpful plot(anova(my.model)) in the rms package provides Wald chi2 - df statistics for each predictor to approximate the penalized LR for each predictor.
Is it at least approximately valid to divide the Wald Chi2-df for the predictor of interest by the sum of Wald Chi2 - df for all the predictors to get this “partial” index?
I have bootstrapped the process to provide medians and 2.5%-97.5% percentiles of the estimates.