mlr_measures_surv.grafSE {mlr3proba}R Documentation

Standard Error of Integrated Graf Score Survival Measure

Description

Calculates the standard error of MeasureSurvGraf.

If integrated == FALSE then the standard error of the loss, L, is approximated via,

se(L) = sd(L)/√ N

where N are the number of observations in the test set, and sd is the standard deviation.

If integrated == TRUE then correlations between time-points need to be taken into account, therefore

se(L) = √((∑_{i = 1}^M∑_{j=1}^M cov(T_i, T_j)) / (NT^2))

where cov(T_i, T_j) is the sample covariance matrix over M distinct time-points.

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

MeasureSurvGrafSE$new()
mlr_measures$get("surv.grafSE")
msr("surv.grafSE")

Meta Information

Super classes

mlr3::Measure -> mlr3proba::MeasureSurv -> mlr3proba::MeasureSurvIntegrated -> MeasureSurvGrafSE

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
MeasureSurvGrafSE$new(integrated = TRUE, times)
Arguments
integrated

(logical(1))
If TRUE (default), returns the integrated score; otherwise, not integrated.

times

(numeric())
If integrate == TRUE then a vector of time-points over which to integrate the score. If integrate == FALSE then a single time point at which to return the score.

Method clone()

The objects of this class are cloneable with this method.

Usage
MeasureSurvGrafSE$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

References

Graf E, Schmoor C, Sauerbrei W, Schumacher M (1999). “Assessment and comparison of prognostic classification schemes for survival data.” Statistics in Medicine, 18(17-18), 2529–2545. doi: 10.1002/(sici)1097-0258(19990915/30)18:17/18<2529::aid-sim274>3.0.co;2-5.

See Also

Other survival measures: mlr_measures_surv.beggC, mlr_measures_surv.calib_alpha, mlr_measures_surv.calib_beta, mlr_measures_surv.chambless_auc, mlr_measures_surv.cindex, mlr_measures_surv.gonenC, mlr_measures_surv.graf, mlr_measures_surv.harrellC, mlr_measures_surv.hung_auc, mlr_measures_surv.intloglossSE, mlr_measures_surv.intlogloss, mlr_measures_surv.logloss_se, mlr_measures_surv.logloss, mlr_measures_surv.maeSE, mlr_measures_surv.mae, mlr_measures_surv.mseSE, mlr_measures_surv.mse, mlr_measures_surv.nagelk_r2, mlr_measures_surv.oquigley_r2, mlr_measures_surv.rmseSE, 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.unoC, mlr_measures_surv.uno_auc, mlr_measures_surv.uno_tnr, mlr_measures_surv.uno_tpr, mlr_measures_surv.xu_r2

Other Probabilistic survival measures: mlr_measures_surv.graf, mlr_measures_surv.intloglossSE, mlr_measures_surv.intlogloss, mlr_measures_surv.logloss_se, mlr_measures_surv.logloss, mlr_measures_surv.schmid

Other distr survival measures: mlr_measures_surv.calib_alpha, mlr_measures_surv.graf, mlr_measures_surv.intloglossSE, mlr_measures_surv.intlogloss, mlr_measures_surv.logloss_se, mlr_measures_surv.logloss, mlr_measures_surv.schmid

[Package mlr3proba version 0.2.6 Index]