diagCI {bootLR} R Documentation

## Compute values and confidence intervals for sensitivity, specificity, positive likelihood ratio, negative likelihood ratio for a single 2x2 table

### Description

Compute values and confidence intervals for sensitivity, specificity, positive likelihood ratio, negative likelihood ratio for a single 2x2 table

### Usage

```diagCI(truePos, totalDzPos, trueNeg, totalDzNeg,
calcLRCI = "BayesianLR.test", alpha = 0.05, binomMethod = "wilson",
...)
```

### Arguments

 `truePos` The number of true positive tests. `totalDzPos` The total number of positives ("sick") in the population. `trueNeg` The number of true negatives in the population. `totalDzNeg` The total number of negatives ("well") in the population. `calcLRCI` Method to use to calculate the LR CI: "BayesianLR.test" "none" or "analytic" `alpha` The alpha for the width of the confidence interval (defaults to alpha = 0.05 for a 95 percent CI) `binomMethod` The method to be passed to binom.confint to calculate confidence intervals of proportions (sensitivity, etc.). See help("binom.confint") and the Newcombe article referenced below. `...` Arguments to pass to Bayesian.LRtest.

### Value

A matrix containing sensitivity, specificity, posLR, negLR results and their confidence intervals

### References

Deeks JJ, Altman DG. BMJ. 2004 July 17; 329(7458): 168-169. Newcombe RG. Statist Med. 1998; 17(857-872).

### Examples

```## Not run:
diagCI( 25, 50, 45, 75 )
diagCI( truePos = c(25, 30), totalDzPos = c( 50, 55 ), trueNeg = c(5, 35), totalDzNeg = c(60,65) )

## End(Not run)
```

[Package bootLR version 1.0.2 Index]