help metandiplot                                                (Roger Harbord)
                                                             also see:  metandi


metandiplot -- SROC plot of results from metandi


metandiplot [ tp fp fn tn] [if] [in] [weight] [, notruncate level(#) predlevel(numlist) npoints(#) subplot_options addplot(plot) twoway_options ]

aweights, fweights, and pweights are allowed; see weight.


metandiplot graphs the results from metandi on a summary receiver operating characteristic (SROC) plot. By default the display includes:

- a summary point showing the summary sensitivity and specificity - a confidence contour outlining the confidence region for the summary point - one or more prediction contours outlining the prediction region for the true sensitivity and specificity in a future study - the HSROC curve from the hierarchical Summary ROC (HSROC) model

If the optional variables tp fp fn tn are included on the command line, the plot also includes study estimates indicating the sensitivity and specificity estimated using the data from each study separately.

Any of these features may be customised or turned off using the subplot_options.


notruncate specificies that the HSROC curve will not be truncated outside the region of the data. By default, the HSROC curve is not shown when the sensitivity or specificity is less than its smallest study estimate.

level(#) specifies the confidence level, in percent, for the confidence contour; see help level.

predlevel(numlist) specifies the levels, in percent, for the prediction contour(s). The default is a single contour at the same probability level as the confidence region. Up to five prediction contours are allowed.

npoints(#) specifies the number of points to use in drawing the outlines of the confidence and prediction regions. The default is 500.

subplot_options: summopts(), confopts(), predopts(), curveopts() and studyopts() specify options that control the display of the summary point, confidence contour, prediction contour(s), HSROC curve and study symbols respectively. The options within each set of parantheses are simply passed through to the appropriate twoway plot. In addition, any of the plots can be turned off by specifying, for example, summopts(off).

addplot(plot) allows adding additional graph twoway plots to the graph; see addplot_option. For example, empirical Bayes predictions could be generated by using predict after metandi and added to the graph. See metandipostestimation.

twoway_options are most of the options documented in twoway_options, including options for titles, axes, labels, schemes and saving the graph to disk. The by() option is not allowed, however.


The default is to weight the study estimates by the total number in each study, giving symbols (open circles by default) scaled according to the size of the weights; see weighted markers. To make the symbols all the same size, specify constant weights, e.g. [aw=1].


. metandiplot

. metandiplot tp fp fn tn

. metandiplot tp fp fn tn [aw=1], conf(off) curve(off) predlevel(50 80 95 99)

Also see