| 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)