Functions to assess the calibration of logistic regression models with the GiViTI (Gruppo Italiano per la Valutazione degli interventi in Terapia Intensiva, Italian Group for the Evaluation of the Interventions in Intensive Care Units - see <http://www.giviti.marionegri.it/>) approach. The approach consists in a graphical tool, namely the GiViTI calibration belt, and in the associated statistical test. These tools can be used both to evaluate the internal calibration (i.e. the goodness of fit) and to assess the validity of an externally developed model.
|Author||Giovanni Nattino [cre, aut], Stefano Finazzi [aut], Guido Bertolini [aut], Carlotta Rossi [aut], Greta Carrara [aut]|
|Date of publication||2016-07-14 07:21:13|
|Maintainer||Giovanni Nattino <email@example.com>|
calibrationBeltIntersections: Calibration Belt Significant Deviations
calibrationBeltPoints: Calibration Belt Confidence Region
givitiCalibrationBelt: Calibration Belt
givitiCalibrationBeltTable: Table of the Calibration Belt Significant Deviations
givitiCalibrationTest: Calibration Test
givitiCalibrationTestComp: Computation of the Calibration Test
givitiCheckArgs: Check of the argument's values
givitiCheckData: Check of data
givitiR: givitiR: assessing the calibration of binary outcome models...
givitiStatCdf: CDF of the Calibration Statistic Under the Null Hypothesis
icuData: Information of SAPS II score and outcome of 1,000 ICU...
logit: Logit and logistic functions
plot.givitiCalibrationBelt: Calibration Belt Plot
polynomialLogRegrFw: Forward Selection in Polynomial Logistic Regression