This calibration method fits the predicted linear predictor from a Cox PH model as the only predictor in a new Cox PH model with the test data as the response. $$h(t|x) = h_0(t)exp(l\beta)$$ where \(l\) is the predicted linear predictor.
The model is well calibrated if the estimated \(\beta\) coefficient is equal to 1.
Assumes fitted model is Cox PH.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
MeasureSurvCalibrationBeta$new() mlr_measures$get("surv.calib_beta") msr("surv.calib_beta")
Type: "surv"
Range: \((-\infty, \infty)\)
Minimize: FALSE
Required prediction: lp
mlr3::Measure
-> mlr3proba::MeasureSurv
-> MeasureSurvCalibrationBeta
new()
Creates a new instance of this R6 class.
MeasureSurvCalibrationBeta$new()
clone()
The objects of this class are cloneable with this method.
MeasureSurvCalibrationBeta$clone(deep = FALSE)
deep
Whether to make a deep clone.
Van Houwelingen, C. H (2000). “Validation, calibration, revision and combination of prognostic survival models.” Statistics in Medicine, 19(24), 3401--3415. 10.1002/1097-0258(20001230)19:24<3401::AID-SIM554>3.0.CO;2-2.
Other survival measures:
mlr_measures_surv.calib_alpha
,
mlr_measures_surv.chambless_auc
,
mlr_measures_surv.cindex
,
mlr_measures_surv.dcalib
,
mlr_measures_surv.graf
,
mlr_measures_surv.hung_auc
,
mlr_measures_surv.intlogloss
,
mlr_measures_surv.logloss
,
mlr_measures_surv.mae
,
mlr_measures_surv.mse
,
mlr_measures_surv.nagelk_r2
,
mlr_measures_surv.oquigley_r2
,
mlr_measures_surv.rcll
,
mlr_measures_surv.rmse
,
mlr_measures_surv.schmid
,
mlr_measures_surv.song_auc
,
mlr_measures_surv.song_tnr
,
mlr_measures_surv.song_tpr
,
mlr_measures_surv.uno_auc
,
mlr_measures_surv.uno_tnr
,
mlr_measures_surv.uno_tpr
,
mlr_measures_surv.xu_r2
Other calibration survival measures:
mlr_measures_surv.calib_alpha
,
mlr_measures_surv.dcalib
Other lp survival measures:
mlr_measures_surv.chambless_auc
,
mlr_measures_surv.hung_auc
,
mlr_measures_surv.nagelk_r2
,
mlr_measures_surv.oquigley_r2
,
mlr_measures_surv.song_auc
,
mlr_measures_surv.song_tnr
,
mlr_measures_surv.song_tpr
,
mlr_measures_surv.uno_auc
,
mlr_measures_surv.uno_tnr
,
mlr_measures_surv.uno_tpr
,
mlr_measures_surv.xu_r2