surv_validate

Computes performance statistics for a survival data given the predicted event probabilities

Performs repeated nested cross-validation for Cox Proportionate Hazards, Cox Lasso, Survival Random Forest, and their ensemble. Returns internally validated concordance index, time-dependent area under the curve, Brier score, calibration slope, and statistical testing of non-linear ensemble outperforming the baseline Cox model. In this, it helps researchers to quantify the gain of using a more complex survival model, or justify its redundancy. Equally, it shows the performance value of the non-linear and interaction terms, and may highlight the need of further feature transformation. Further details can be found in Shamsutdinova, Stamate, Roberts, & Stahl (2022) "Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes" <doi:10.1007/978-3-031-08337-2_15>, where the method is described as Ensemble 1.

Diana Shamsutdinova

survcompare

Compares Cox and Survival Random Forests to Quantify
Nonlinearity

Daniel Stahl

surv_validate function

<dl><dt>y_predict</dt>
<dd>probabilities of event by predict_time (matrix=observations x times)</dd>
<dt>predict_time</dt>
<dd>times for which event probabilities are given</dd>
<dt>df_train</dt>
<dd>train data, data frame</dd>
<dt>df_test</dt>
<dd>test data, data frame</dd>
<dt>weighted</dt>
<dd>TRUE/FALSE, for IPWC</dd>
<dt>alpha</dt>
<dd>calibration alpha as mean difference or from logistic regression</dd></dl>

Arguments

Computes performance statistics for a survival data given the predicted event probabilities — surv_validate

<dl>

<dt>y_predict</dt>
<dd>probabilities of event by predict_time (matrix=observations x times)</dd>


<dt>predict_time</dt>
<dd>times for which event probabilities are given</dd>


<dt>df_train</dt>
<dd>train data, data frame</dd>


<dt>df_test</dt>
<dd>test data, data frame</dd>


<dt>weighted</dt>
<dd>TRUE/FALSE, for IPWC</dd>


<dt>alpha</dt>
<dd>calibration alpha as mean difference or from logistic regression</dd>

</dl>

surv_validate: Computes performance statistics for a survival data given the predicted event probabilities

Description

Usage

Value

Arguments