Accuracy of a Single Binary Diagnostic Test
acc.1test.Rd
Sensitivity and specificity, (positive and negative) predictive values and (positive and negative) diagnostic likelihood ratios of a single binary diagnostic test.
Arguments
- tab
An object of class
tab.1test
.- alpha
Significance level alpha for 100(1-alpha)%-confidence intervals, the default is 0.05.
- testname
A character variable containing the name of the diagnostic test.
- ...
Additional arguments (usually not required).
Details
The calculation of accuracy measures and their variances follows standard methodology, e.g. described in Pepe (2003) or Zhou et al. (2011). Confidence intervals for diagnostic likelihood ratios are computed according to Simel et al. (1991).
Value
A list of class acc.1test
:
- tab
A contingency table (matrix) of test results; the same
tab
that is supplied as an argument.Diseased Non-diseased Total Test pos. ... ... ... Test neg. ... ... ... Total ... ... ... - sensitivity
A numeric vector containing the estimated sensitivity (
est
), its standard error (se
), lower confidence limit (lcl
) and upper confidence limit (ucl
).- specificity
A numeric vector containing the estimated specificity (
est
), its standard error (se
), lower confidence limit (lcl
) and upper confidence limit (ucl
).- ppv
A numeric vector containing the estimated positive predictive value (
est
), its standard error (se
), lower confidence limit (lcl
) and upper confidence limit (ucl
).- npv
A numeric vector containing the estimated negative predictive value (
est
), its standard error (se
), lower confidence limit (lcl
) and upper confidence limit (ucl
).- pdlr
A numeric vector containing the estimated positive diagnostic likelihood ratio (
est
), the standard error of the logarithm of the positive diagnostic likelihood ratio (se.ln
), the lower confidence limit (lcl
) and the upper confidence limit (ucl
).- ndlr
A numeric vector containing the estimated negative diagnostic likelihood ratio (
est
), the standard error of the logarithm of the negative diagnostic likelihood ratio (se.ln
), the lower confidence limit (lcl
) and the upper confidence limit (ucl
).- alpha
The significance level alpha used to compute 100(1-alpha)%-confidence intervals, the default is 0.05.
- testname
A character variable containing the name of the diagnostic test.
References
Pepe, M. (2003). The statistical evaluation of medical tests for classification and prediction. Oxford Statistical Science Series. Oxford University Press, 1st edition.
Simel, D.L., Samsa, G.P., Matchar, D.B. (1991). Likelihood ratios with confidence: sample size estimation for diagnostic test studies. J Clin Epidemiol, 44(8):763-70.
Zhou, X., Obuchowski, N., and McClish, D. (2011). Statistical Methods in Diagnostic Medicine. Wiley Series in Probability and Statistics. John Wiley & Sons, Hoboken, New Jersey, 2nd edition.
Examples
data(Paired1) # Hypothetical study data
a1 <- tab.1test(d=d, y=y1, data=Paired1)
a2 <- acc.1test(a1)
print(a2)
#> Diagnostic accuracy of test 'y1'
#>
#> (Estimates, standard errors and 95%-confidence intervals)
#>
#> Est. SE Lower CL Upper CL
#> Sensitivity 0.8802661 0.01528718 0.8503038 0.9102284
#> Specificity 0.6781609 0.02891782 0.6214830 0.7348388
#> PPV 0.8253638 0.01731081 0.7914353 0.8592924
#> NPV 0.7662338 0.02784617 0.7116563 0.8208113
#>
#> Est. SE (log) Lower CL Upper CL
#> PDLR 2.7351124 0.0915147 2.2860079 3.2724472
#> NDLR 0.1765568 0.1346088 0.1356142 0.2298601