diagCI function

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

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.

Returns

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

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)

References

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