the same correlation structure. When comparing QICu values from two models, it can be inferred that the model with a smaller QICu accounts more adequately for the relationship between predictor(s) and outcome. Moreover, in comparing models with different numbers of predictors, the QICu for the more complex model is penalized for added predictors; this balances the trade-off between goodness of fit and model-complexity. For instance, when we add PLF to EVK in our models, a smaller value of QICu relative to the simpler EVK-only model would indicate that adding PLF to the model effectively offsets the penalty incurred by having added a second parameter, leading one to infer that the more complex model accounts for the data better than the simpler one.
