Calculate area under the empirical pseudo-type 1 receiver operating characteristic curve

Calculate area under the empirical pseudo-type 1 receiver operating characteristic curve

Usage

auroc1(
  data,
  ...,
  .stimulus = "stimulus",
  .response = "response",
  .confidence = "confidence",
  .joint_response = "joint_response",
  K = NULL
)

Arguments

data

The data frame to aggregate

...

Grouping columns in data. These columns will be converted to factors.

.stimulus

The name of "stimulus" column

.response

The name of "response" column

.confidence

The name of "confidence" column

.joint_response

The name of "joint_response" column

K

The number of confidence levels in data. If NULL, this is estimated from data using the maximum value of either the confidence column or joint response column.

Value

A tibble with columns:

• ...: the grouping columns in data

• auroc1: the area under the pseudo type 1 ROC curve

See also

roc1(), auroc1_draws(), auroc1_rvars()

Examples

# calculate area under the type 1 ROC
auroc1(example_data())
#> `hmetad` has inferred that there are K=4 confidence levels in the data. If this is incorrect, please set this manually using the argument `K=<K>`
#> # A tibble: 1 × 1
#>   auroc1
#>    <dbl>
#> 1  0.766

# calculate type 1 ROCs by condition
auroc1(sim_metad_condition(), condition)
#> `hmetad` has inferred that there are K=4 confidence levels in the data. If this is incorrect, please set this manually using the argument `K=<K>`
#> # A tibble: 2 × 2
#>   condition auroc1
#>       <int>  <dbl>
#> 1         1  0.689
#> 2         2  0.732