Calculates the Negative Likelihood Ratio (LR-) from a confusion matrix object. LR- compares the probability of a negative test result among patients with the disease to the probability of a negative test result among patients without the disease.
Arguments
- cm
A dx_cm object created by
dx_cm().- detail
Character specifying the level of detail in the output: "simple" for raw estimate, "full" for detailed estimate including 95% confidence intervals.
- ...
Additional arguments to pass to metric_binomial function, such as
citypefor type of confidence interval method.
Value
Depending on the detail parameter, returns a numeric value
representing the calculated metric or a data frame/tibble with
detailed diagnostics including confidence intervals and possibly other
metrics relevant to understanding the metric.
Details
The negative likelihood ratio is calculated as (FN / (TP + FN)) / (TN / (FP + TN)). It is used to assess the diagnostic usefulness of a test. A LR- closer to 0 indicates a good diagnostic test that can confidently rule out the disease when the test is negative.
Examples
cm <- dx_cm(dx_heart_failure$predicted, dx_heart_failure$truth,
threshold =
0.5, poslabel = 1
)
simple_lrn <- dx_lrt_neg(cm, detail = "simple")
detailed_lrn <- dx_lrt_neg(cm)
print(simple_lrn)
#> [1] 0.3326531
print(detailed_lrn)
#> # A tibble: 1 × 8
#> measure summary estimate conf_low conf_high fraction conf_type notes
#> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr>
#> 1 LRT- 0.33 (0.25, 0.45) 0.333 0.246 0.450 "" Large sa… ""