help metandiplot                                                (Roger Harbord)
                                                             also see:  metandi
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Title

    metandiplot -- SROC plot of results from metandi


Syntax

        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.


Description

    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.


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.


Remarks

    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].


Examples

    . metandiplot

    . metandiplot tp fp fn tn

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


Also see