concordance_indices: Computes the conditional Boyce index for model evaluation

In NINAnor/oneimpact: Tools for the assessment of the cumulative impacts of anthropogenic features in ecological studies

Computes the conditional Boyce index for model evaluation

Description

These functions compute different concordance indices.

Usage

conditionalBoyce(
  x,
  method = c("pearson", "kendall", "spearman")[1],
  plotit = FALSE,
  errors = TRUE,
  warnings = TRUE
)

conditionalSomersD(x, errors = TRUE, warnings = TRUE)

conditionalAUC(x, errors = TRUE, warnings = TRUE)

AUC(x, errors = TRUE, warnings = TRUE)

coxnet.deviance(x, errors = TRUE, warnings = TRUE)

Cindex(x, errors = TRUE, warnings = TRUE)

Arguments

x	A data.frame with three columns: x, the predicted values; y, the case variable (use vs. available, 1/0); and strat, the stratum.

Details

The function conditionalAUC() is the implementation of the computation of the Area Under the Curve as related to the Sommers'D index, as described in https://cran.r-project.org/web/packages/survival/vignettes/concordance.pdf. It is implemented by accounting for strata, ideal for conditional logistic regression, but it is under testing. The function AUC() uses the pROC::auc() function and does not account for strata. Functions conditionalBoyce and conditionalSomersD both account for strata, but are under checking. The functions coxnet.deviance and Cindex are wrappers for the same functions from glmnet, which are suitable for cox models, but here they use the same arguments as all the other concordance variables.

References

https://cran.r-project.org/web/packages/survival/vignettes/concordance.pdf

See Also

conditionalBoyce

NINAnor/oneimpact documentation built on June 14, 2025, 12:27 a.m.