help bcii and help bcib                                  Version 1.1 31-05-2009

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Title

    bcii -- Calculates the number needed to treat (NNT) and confidence
            intervals for patients improving (comparison between intervention
            and control group in a randomised controlled trial)
    bcib -- Calculates NNT and confidence intervals for patients benefiting
            (either improvements gained or deteriorations prevented) in a
            randomised controlled trial


Syntax

        bcii #a #b #c #d [, options]

        bcib #a #b #c #d #e #f #g #h [, options]

    options               Description
    -------------------------------------------------------------------------
    Main
      level(#)            set confidence level; default is prevailing setting
                            (see creturn)


Descriptions

    bcii estimates absolute risk reduction and number needed to treat for for
    the difference between the proportion of improving patients in the
    intervention group and the proportion of improving patients in the
    control group. It uses a method that is considered to have superior
    coverage properties to the conventional Wald method for calculating
    confidence intervals (Newcombe's Method 10); this may be important when
    reciprocally transforming absolute risk reductions to obtain numbers
    needed to treat (NNTs) as described by Bender, 2001.  estimates NNTs for
    benefit; the difference between the proportion of improving patients
    minus the proportion of deteriorating patients in the intervention group
    and the proportion of improving patients minus the proportion of
    deteriorating patients in the control group. Newcombe's method 10 has
    been modified to incorporate these extra variance terms as described by
    Froud et al, 2009.

Options

        +------+
    ----+ Main +-------------------------------------------------------------

    level set confidence level; it must lie between 0.1 and 99.9%, inclusive;
        default is the Stata level setting.

Remarks

    bcii calculates confidence intervals for the NNT by reciprocal
    transformation of risk difference confidence intervals, from differences
    between two independent proportions (patients improving in the treatment
    group and in the control group)using Newcombe's Method 10. The confidence
    intervals are considered to have better coverage than the conventional
    Wald confidence interval and are less prone to aberrations following
    reciprocal transformation to NNT limits.

    The sequence of #a, #b, #c and #d in bcii come from a contingency table
    of 'improvements' x group (see epitab). The additional #a, #b, #c and #d
    in bcib come from a similar table of 'deteriorations' (see epitab).



Examples

    . bcii 82 62 143 194

    . bcii 82 62 143 194, level(90)

    . bcib 82 62 143 194 5 12 220 243


References

    R. Froud, S. Eldridge, R.Lall, M.Underwood, Estimating NNT from
    continuous outcomes in randomised controlled trials: Methodological
    challenges and worked example using data from the UK Back Pain Exercise
    and Manipulation (BEAM) trial ISRCTN32683578. BMC Health Services
    Research 2009 IN PRESS.

    R. Bender, Calculating confidence intervals for the Number Needed to
    Treat Controlled clinical trials 22-102-110, 2001.


    R. G. Newcombe, Interval estimation for the difference between
    independent proportions:  comparison of eleven methods. Statistics in
    Medicine 17:873-90, 1998.


Acknowledgements

    Code for calculating Wilson intervals of the individual proportions (used
    in calculation of Newcombe's Method 10 confidence intervals) is adapted
    from rdcii by Joseph Coveney, who adapted code from ciwi by Nicholas J.
    Cox. Thanks to my colleagues, S. Eldridge, R.Lall, and M.Underwood for
    their help and comments on the modifications to Newcombe's Method 10, and
    to Gordon Guyatt, Thomas Kottke, and Kamshwar Prasad, for their very
    useful comments on the accompanying paper; and to Mandy Hildebrandt and
    Michal Vaillant for their comments on an earlier version of the paper.


Author

    Robert Froud r.j.froud@qmul.ac.uk


Also see

    Manual:  [ST] epitab