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Samples data for a prediction model with a specified AUC and prevalence.

Usage

get_sample(auc, n_samples, prevalence, min_events = 0)

Arguments

auc

The Area Under the (receiver operating characteristic) Curve.

n_samples

Number of samples to draw.

prevalence

Prevalence or event rate of the binary outcome as a proportion (0.1 = 10%).

min_events

Minimum number of events required in the sample.

Value

Returns a data.frame.

Examples

get_sample(0.7, 1000, 0.1)
#>                  x actual
#> 1    -0.8416833722      0
#> 2     0.0765382119      0
#> 3    -0.1922890419      0
#> 4     0.3570301790      0
#> 5    -1.0747851799      0
#> 6    -0.7412112881      0
#> 7    -1.1228880099      0
#> 8    -0.8640324497      0
#> 9     0.4151569276      0
#> 10   -1.1281922187      0
#> 11   -0.4775184838      0
#> 12   -0.4547828540      0
#> 13    1.0091338791      0
#> 14    0.8396342719      0
#> 15   -1.1193198384      0
#> 16   -0.3068668509      0
#> 17    0.1994008299      0
#> 18    2.3647743516      0
#> 19   -0.4523329259      0
#> 20   -0.9664538927      0
#> 21   -0.1048319138      0
#> 22    0.5510409941      0
#> 23    0.1562973543      0
#> 24   -1.5560664748      0
#> 25    0.4620669578      0
#> 26    3.1118371525      0
#> 27    0.6255521376      0
#> 28    1.5427920308      0
#> 29   -0.9633823185      0
#> 30   -0.4740360710      0
#> 31    0.6635689746      0
#> 32   -0.6558185045      0
#> 33    0.3058048837      0
#> 34   -0.2300694075      0
#> 35   -0.5430605908      0
#> 36    1.8003554495      0
#> 37   -0.4940561235      0
#> 38   -1.6588393613      0
#> 39    0.6044759828      0
#> 40   -2.0862850159      0
#> 41   -1.6124623978      0
#> 42    0.0500710574      0
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#> 190  -0.3994700955      0
#> 191   1.1174693725      0
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#> 250  -0.3320099864      0
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#> 539  -0.2201325501      0
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