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# Effect of fibre, antispasmodics, and peppermint oil in the treatment of irritable bowel syndrome: systematic review and meta-analysis

BMJ 2008; 337 (Published 14 November 2008) Cite this as: BMJ 2008;337:a2313

## Rapid Response:

### Re: Re: Forest plot: not seeing the wood for the logs

I thank Professor Altman for his response, since science cannot
progress without scepticism- or debate.

The lie factor is not Einstein with graphs! Take, for example, a meta
- analysis where the relative risks are all between 1 and 2. Then a spaced
out x- axis to log base two will make the figures seem move removed from
the y- axis than an x- axis to log base ten. Of course, the real data are
the same, but the appearances? Ha! It is just a mere visual thing, it is
not high powered mathematics (1). Some relative risks in forest plots are
on a linear axis, and then we would have all sorts of distortions to the
confidence intervals. The mathematical problem is that the standard error,
and therefore the confidence interval, with relative risk (as a ratio) is
logarithmic (base e).
Statistical theory would be impossible without that natural log, e.

As for numbers needed to treat, this seems a practical down to earth
sort of way for clinicians to examine data. That a meta- analysis,
according to Professor Altman, is unable to include numbers needed to
treat is a sign something is deficient about the excessively theoretical
nature of a meta- analysis.

What of absolute risk difference? Again, the way this looks visually
would alter according to what sort of x- axis lay out we had. The damned
lies label on statistics derives from spinning identical data, often
through graphs, to make it look different- quite unjustifiably.

REFERENCES:

The Cambridge Dictionary of Statistics in the Medical sciences. B. S.
Everitt. 1995. Pg. 142.

'Lie factor=apparent size of effect show in graph divided by actual
size of effect in data'

Competing interests:
None declared

Competing interests: No competing interests

18 May 2009
Ibrahimi Zekria
psychiatric patient
Coombs Library