`calibrateLlr`

computes calibrated log likelihood ratio using the fitted null distribution

`calibrateLlr(null, likelihoodApproximation, twoSided = FALSE, upper = TRUE)`

## Arguments

- null
An object of class `null`

created using the `fitNull`

function or an
object of class `mcmcNull`

created using the `fitMcmcNull`

function.

- likelihoodApproximation
Either a data frame containing normal, skew-normal, or custom parametric likelihood
approximations, or a list of (adaptive) grid likelihood profiles.

- twoSided
Compute two-sided (TRUE) or one-sided (FALSE) p-value?

- upper
If one-sided: compute p-value for upper (TRUE) or lower (FALSE) bound?

## Value

The calibrated log likelihood ratio.

## Examples

```
data(sccs)
negatives <- sccs[sccs$groundTruth == 0, ]
null <- fitNull(negatives$logRr, negatives$seLogRr)
positive <- sccs[sccs$groundTruth == 1, ]
calibrateLlr(null, positive)
#> Detected data following normal distribution
#> [1] 0
```