meta4diag (version 2.1.1)

AUC: A function that calculate the area under summary receiver operating chracteristic line.

Description

Takes a meta4diag object produced by meta4diag() and calculate the area under summary receiver operating chracteristic line.

Usage

# S3 method for meta4diag
AUC(x, sroc.type=1, est.type="median", ...)

Arguments

x

A meta4diag object.

est.type

The estimates type used to make SROC plot. Options are "mean" and "median".

sroc.type

A numerical value specifying the function used to make SROC line. Options are 1, 2, 3, 4, 5. When sroc.type=1, the SROC line is plotted as " The regression line 1" according to Arends et al.(2008), $$y = \mu + \rho\sqrt{\frac{\sigma_{\mu}^2}{\sigma_{\nu}^2}}(x-\nu)$$ When sroc.type=2, the SROC line is plotted as "The major axis method", $$y = \frac{\sigma_{\mu}^2-\sigma_{\nu}^2\pm\sqrt{(\sigma_{\mu}^2-\sigma_{\nu}^2)^2+4\rho^2\sigma_{\mu}^2\sigma_{\nu}^2}}{2\rho\sqrt{\sigma_{\mu}^2\sigma_{\nu}^2}}(x-\nu)+\mu$$ When sroc.type=3, the SROC line is plotted as "The Moses and Littenberg's regression line", $$y = \frac{\sigma_{\mu}^2 + \rho\sqrt{\sigma_{\mu}^2\sigma_{\nu}^2}}{\sigma_{\nu}^2+\rho\sqrt{\sigma_{\mu}^2\sigma_{\nu}^2}}(x-\nu)+\mu$$ When sroc.type=4, the SROC line is plotted as "The regression line 2", $$y = \mu + \frac{1}{\rho}\sqrt(\frac{\sigma_{\mu}^2}{\sigma_{\nu}^2})(x-\nu)$$ When sroc.type=5, the SROC line is plotted as "The Rutter and Gatsonis's SROC curve", $$y = \mu + \sqrt{\frac{\sigma_{\mu}^2}{\sigma_{\nu}^2}}(x-\nu)$$

…

Arguments to be passes to methods.

Value

A vector containing the "est", which indicate the estimates of AUC of the estimated SROC vurve and "mean" and "sd" (plus, possibly quantiles) of AUC if nsample is given.

Details

The AUC() returns an estimate of the area under the SROC curve. When the number of samples is given in the makeObject() or meta4diag(), the uncertainty of AUC is estimated. Otherwise only the estimates of the AUC respect to the estimated SROC curve is returned.

References

Chappell F, Raab G, Wardlaw J (2009). "When are Summary ROC Curves Appropriate for Diagnostic Meta-analyses?" Statistics in Medicine, 28(21), 2653-2668.

Arends et al.(2008) "Bivariate random effects meta-analysis of ROC curves." Medical Decision Making, 28(5), 621-638.

See Also

SROC, meta4diag

Examples

# NOT RUN {
if(requireNamespace("INLA", quietly = TRUE)){
  require("INLA", quietly = TRUE)
  data(Catheter)
  res <- meta4diag(data = Catheter, nsample=1000)
  AUC(res, est.type="mean")
}
# }