Calculated a permuted p-value comparing two models
Usage
permute_p_value(
merged_data,
metric,
group_name,
group_1,
group_2,
nperm = 10000
)
Arguments
- merged_data
the concatenated performance data from run_ml
- metric
metric to compare, must be numeric
- group_name
column with group variables to compare
- group_1
name of one group to compare
- group_2
name of other group to compare
- nperm
number of permutations, default=10000
Value
numeric p-value comparing two models
Examples
df <- dplyr::tibble(
model = c("rf", "rf", "glmnet", "glmnet", "svmRadial", "svmRadial"),
AUC = c(.2, 0.3, 0.8, 0.9, 0.85, 0.95)
)
set.seed(123)
permute_p_value(df, "AUC", "model", "rf", "glmnet", nperm = 100)
#> [1] 0.3663366
