Comparison of strategies for validating binary logistic regression models

06-Jul-2017 21:53

The authors hypothesize that the model used to develop SAPS 3 was not able to adequately take account of factors such as differences in case-mix, influence of unmeasured context-sensitive variables, and the phenomenon of overfitting, but regrettably such questions remain unanswered. focused in this study on the comparison between SAPS II and SAPS 3, in our opinion the main relevance of their work is to introduce the implementation of the calibration belt approach [] as a new calibration-assessment tool.Calibration of SAPS II and SAPS 3 mortality predictions was measured using the new method.Second, to localize possible deviations across risk strata by means of calibration plots with observed outcomes versus expected probabilities of mortality.The calibration plot, also named calibration curve, intends to provide complementary information over subsets.The H–L test is easy to compute and its interpretation is intuitive, but it has acknowledged limitations such as being very sensitive to sample size [].

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In this way, continuous improvements in health care possibly have a bigger impact on sicker patients, whereas unchanged conventional treatments have been given to low-risk patients since a long time ago.Calibration measures the model’s ability to generate predictions that are on average close to the average observed outcome.Calibration has traditionally been approached in two steps.The authors have made an empiric demonstration of this new statistical tool to assess the dependence of calibration on the expected probability by plotting the corresponding curve and its confidence band.