help midas rgsrocalso see: midas

Title

midas rgsroc -- Rutter-Gatsonis HSROC curve

Syntax

midas rgsroc
[if exp]
[in range]
[, options]

Curve bands
cbounds pointwise confidence bounds around the SROC curve

cregion confidence band as a shaded area; color via crcolor()

pbounds pointwise prediction bounds

pregion prediction band as a shaded area; color via prcolor()

crcolor(colorstyle) color for confidence region; default blue%30

prcolor(colorstyle) color for prediction region; default green%30

Curve styling
curveopts(line_options) options for the SROC curve line

Study points
data overlay observed (Se, 1-Sp) study points

weighted size study markers by inverse-variance weight

labeldata label each study point with its sequence number

pointopts(scatter_options) marker options for the study scatter points

Legend and layout
lgnd display a legend

lgnpos(#) legend position; default lgnpos(6)

level(#) confidence/prediction level; default level(95)

graph_options any twoway options

Description

midas rgsroc plots the Rutter-Gatsonis hierarchical SROC (HSROC) curve
after a midas mle, midas qrsim, midas mh, midas hmc,
or midas inla estimation command. Sensitivity is on the y-axis,
specificity (reversed) on the x-axis. The curve and its confidence and
prediction bounds are constructed from the HSROC parameterisation (alpha,
theta, beta, sigma²_alpha, sigma²_theta) recovered via the delta method from
the bivariate random-effects estimates.

cbounds/cregion are mutually exclusive; so are pbounds/pregion.

Options

cbounds draws dashed pointwise confidence bounds for the SROC curve.
Default color is blue.

cregion draws the confidence band as a shaded area. Default color is
blue%30; override with crcolor().

pbounds draws dashed pointwise prediction bounds. Default color is green.

pregion draws the prediction band as a shaded area. Default color is
green%30; override with prcolor().

curveopts(line_options) overrides the default SROC curve style
(solid black thick line), e.g. curveopts(lcolor(maroon) lwidth(medthick)).

pointopts(scatter_options) overrides the default study point
style, e.g. pointopts(mcolor(navy) msymbol(circle_hollow)).

Returned results

r(AUC) area under the SROC curve

r(AUClo) lower confidence bound for AUC

r(AUChi) upper confidence bound for AUC

Examples

SROC curve with prediction region and study points:

. midas mle tp fp fn tn, id(author)

. midas rgsroc, data pregion weighted

Custom curve and point colors:

. midas rgsroc, data cbounds curveopts(lcolor(maroon) lwidth(medthick)) pointopts(mcolor(navy))

References

Rutter CM, Gatsonis CA. A hierarchical regression approach to meta-analysis
of diagnostic test accuracy evaluations. Statistics in Medicine
2001;20:2865–2884.
https://doi.org/10.1002/sim.942

Harbord RM, Deeks JJ, Egger M, Whiting P, Sterne JAC. A unification of models
for meta-analysis of diagnostic accuracy studies. Biostatistics
2007;8:239–251.
https://doi.org/10.1093/biostatistics/kxl004

Also see

midas, midas bvsroc, midas forest