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Statistical Software for Medical Research in the
21st Century
Iain E Buchan
CamCode, £99 single user academic, £179 single user commercial, £49 students and developing world






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Clinicians involved in medical research are
increasingly numerate and statistically sophisticated. Recently, two
colleagues hounded me. They wanted to see confidence intervals for
every number in a paper describing a randomised trial that we had
worked on together. I found myself in a strange position In part, this increased sophistication is due to the availability of
accessible and intuitive statistical packages. StatsDirect is an addition that can be used by those without the questionable luxury of a PhD in statistics and a spare year or two to learn a new
programming language.
StatsDirect performs a range of functions, including sample
size calculations, exact 95% confidence intervals for odds ratios, numbers needed to treat, non-parametric analyses, and survival analysis
methods. A host of useful features, such as t tests from summary data, make it valuable for reviewing research.
Its greatest value is its functionality Its main disadvantage is that it does not provide a programming
language and a range of model specifications, a limitation particularly
important for generalised linear modelling. There are, however, other
packages that can address this requirement, but surprisingly few can
make statistical analyses available to a broad range of researchers, as
this package does.
the
confidence intervals that they wanted were neither straightforward nor
ultimately appropriate, but it was pleasing to be asked for them after
years of emphasising the importance of estimation rather than
hypothesis testing.
one colleague used it to
perform a meta-analysis in a matter of minutes. Statistical novices
will probably find the package straightforward to use. It also does a
good job of keeping up to date with new methods. After recent work on
analysis of cost data in clinical trials published in the
BMJ, the program's author agreed to add non-parametric bootstrap confidence intervals as a feature for a future release of the package.
Footnotes
Competing interests: NF provided advice to the author on the development of meta-analysis methods. Neither he nor his department received any financial reward for this work beyond a complementary copy of the package.
Nick Freemantle Medicines Evaluation Group, University of York
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What can you learn from this BMJ paper? Read Leanne Tite's Paper+