Estimate significance of AUC by resampling test.
resampleTestAUC( d, modelName, yName, yTarget = TRUE, ..., na.rm = FALSE, returnScores = FALSE, nrep = 100, parallelCluster = NULL )
| d | data.frame |
|---|---|
| modelName | character model column name |
| yName | character outcome column name |
| yTarget | target to match to y |
| ... | extra arguments (not used) |
| na.rm | logical, if TRUE remove NA values |
| returnScores | logical if TRUE return detailed resampledScores. |
| nrep | number of permutation repetitions to estimate p values. |
| parallelCluster | (optional) a cluster object created by package parallel or package snow. |
AUC statistic
set.seed(25325) d <- data.frame(x1=c(1,2,3,4,5,6,7,7), y=c(FALSE,TRUE,FALSE,FALSE, TRUE,TRUE,FALSE,TRUE)) resampleTestAUC(d,'x1','y',TRUE)#> [1] "AUC test alt. hyp. AUC>0.5: (AUC=0.6562, s.d.=0.2188, p=n.s.)."