crosshair: Crosshair plot

In mada: Meta-Analysis of Diagnostic Accuracy

Crosshair plot

Description

Produces a crosshair plot or adds such a plot to an existing plot.

Usage

## Default S3 method:
crosshair(x, correction = 0.5, level = 0.95, method = "wilson",
                      xlim = c(0,1), ylim = c(0,1), length = 0.1, pch = 1, 
                      add = FALSE, suppress = TRUE, ...)

Arguments

x	a data frame with variables including TP, FN, FP, TN, alternatively a matrix with column names including these.
correction	numeric, continuity correction applied to zero cells.
level	numeric, confidence level for the calculations of confidence intervals.
method	character, method used to calculate the confidence intervals for sensitivities, specificities and false positive rates. One of "wald", "wilson", "agresti-coull", "jeffreys", "modified wilson", "modified jeffreys", "clopper-pearson", "arcsine", "logit", "witting"
xlim	part of ROC space to be plotted
ylim	part of ROC space to be plotted
length	length of "whiskers" of the crosshair.
pch	Symbol used to plot point estimates. Use pch = "" to suppress plotting point estimates.
add	logical, should the plot be added to the current plot?
suppress	logical, should the warnings produced by the internal call to madad be suppressed? Defaults to TRUE, since only the diagnostic accuracies and their confidence intervals are used in subsequent calculations.
...	further arguments passed on to plot.

Details

Crosshair plots go back to Phillips et al. (2010). Note that for fits of the reitsma function a crosshair method is available to plot pooled estimate, see reitsma-class.

Value

Besides plotting, the function returns an invisible NULL.

Author(s)

Philipp Doebler <[e-mail]>

References

Phillips, B., Stewart, L.A., & Sutton, A.J. (2010). “'Cross hairs' plots for diagnostic meta-analysis.” Research Synthesis Methods, 1, 308–315.

See Also

ROCellipse, reitsma-class

Examples

data(AuditC)
crosshair(AuditC)

mada documentation built on Sept. 9, 2022, 3:01 p.m.