R: Uno's TNR Survival Measure

mlr_measures_surv.uno_tnr {mlr3proba} | R Documentation

## Uno's TNR Survival Measure

### Description

Calls `survAUC::spec.uno()`.

Assumes random censoring.

`times` and `lp_thresh` are arbitrarily set to `0` to prevent crashing, these should be further specified.

### Details

All measures implemented from survAUC should be used with care, we are aware of problems in implementation that sometimes cause fatal errors in R. In future updates these measures will all be re-written and implemented directly in `mlr3proba`.

### Dictionary

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

    MeasureSurvUnoTNR$new()
    mlr_measures$get("surv.uno_tnr")
    msr("surv.uno_tnr")

### Meta Information

- Type: `"surv"`

- Range: [0, 1]

- Minimize: `FALSE`

- Required prediction: `lp`

### Super classes

`mlr3::Measure` -> `mlr3proba::MeasureSurv` -> `mlr3proba::MeasureSurvIntegrated` -> `mlr3proba::MeasureSurvAUC` -> `MeasureSurvUnoTNR`

### Active bindings

`lp_thresh`

  `numeric(1)`
  Threshold for linear predictor when calculating TPR/TNR.

### Methods

#### Public methods

- `MeasureSurvUnoTNR$new()`

- `MeasureSurvUnoTNR$clone()`

Inherited methods

- `mlr3::Measure$aggregate()`

- `mlr3::Measure$format()`

- `mlr3::Measure$help()`

- `mlr3::Measure$score()`

- `mlr3proba::MeasureSurv$print()`

#### Method `new()`

Creates a new instance of this R6 class.

##### Usage

    MeasureSurvUnoTNR$new(times = 0, lp_thresh = 0)

##### Arguments

`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.

`lp_thresh`

  `numeric(1)`
  Determines where to threshold the linear predictor for calculating the TPR/TNR.

#### Method `clone()`

The objects of this class are cloneable with this method.

##### Usage

    MeasureSurvUnoTNR$clone(deep = FALSE)

##### Arguments

`deep`

  Whether to make a deep clone.

### References

Uno H, Cai T, Tian L, Wei LJ (2007). “Evaluating Prediction Rules fort-Year Survivors With Censored Regression Models.” Journal of the American Statistical Association, 102(478), 527–537. doi: 10.1198/016214507000000149.

### See Also

Other survival measures: `mlr_measures_surv.calib_alpha`, `mlr_measures_surv.calib_beta`, `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.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_tpr`, `mlr_measures_surv.xu_r2`

Other lp survival measures: `mlr_measures_surv.calib_beta`, `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_tpr`, `mlr_measures_surv.xu_r2`

Other AUC survival measures: `mlr_measures_surv.chambless_auc`, `mlr_measures_surv.hung_auc`, `mlr_measures_surv.song_auc`, `mlr_measures_surv.song_tnr`, `mlr_measures_surv.song_tpr`, `mlr_measures_surv.uno_auc`, `mlr_measures_surv.uno_tpr`

[Package mlr3proba version 0.4.2 Index]