sensSpec {epibasix}R Documentation

Sensitivity and Specificity Analysis of a 2x2 Matrix

Description

This function provides detailed information regarding the comparison of two competing methods, for example self-report and gold-standard treatment through a sensitivity/specificity analysis.

Usage

sensSpec(X, alpha=0.05, CL=TRUE, digits=3)

Arguments

X A 2x2 matrix, with Gold Standard Class A and B in the columns and Comparison Method A and B in the rows.
CL Logical: If TRUE, Confidence Intervals are calculated and displayed in summary method.
alpha The desired Type I Error Rate for Hypothesis Tests and Confidence Intervals
digits Number of Digits to round calculations

Details

This function is designed to calculate Sensitivity, Specificity, Youden's J and Percent Agreement. These tools are used to assess the validity of a new instrument or self-report against the current gold standard. In general, self-report is less expensive, but may be subject to information bias. Computational formulae can be found in the reference.

Value

X The original input matrix.
sens The point estimate of sensitivity
spec The point estimate of specificity
PA The point estimate of Percent Agreement
YoudenJ The point estimate of Youden's J
sens.s The standard deviation of sensitivity
spec.s The standard deviation of specificity
PA.s The standard deviation of Percent Agreement
YoudenJ.s The standard deviation of Youden's J
sens.CIL The lower bound of the constructed confidence interval for true sensitivity.
sens.CIU The upper bound of the constructed confidence interval for true sensitivity
spec.CIL The lower bound of the constructed confidence interval for true specificity.
spec.CIU The upper bound of the constructed confidence interval for true specificity.
PA.CIL The lower bound of the constructed confidence interval for Percent Agreement.
PA.CIU The upper bound of the constructed confidence interval for Percent Agreement.
YoudenJ.CIL The lower bound of the constructed confidence interval for Youden's J.
YoudenJ.CIU The upper bound of the constructed confidence interval for Youden's J.
alpha The desired Type I Error Rate for Hypothesis Tests and Confidence Intervals
digits Number of Digits to round calculations

Note

All confidence limits rely on simple asymptotic theory, as such, confidence limits may lie outside of [0,1]. A more accurate method is available in the twoby2 function of the Epi package, which employs a logit transformation.

Author(s)

Michael Rotondi, mrotondi@uwo.ca

References

Szklo M and Nieto FJ. Epidemiology: Beyond the Basics, Jones and Bartlett: Boston, 2007.

See Also

kappa

Examples

## Not run: From Szklo and Nieto, p. 315
dat <- cbind(c(18,1), c(19,11));
summary(sensSpec(dat));

[Package epibasix version 1.1 Index]