Statistical methods in clinical trials

To the Editor: Gebski and Keech describe with clarity and accuracy the important basic concepts of statistical analysis for physicians.1 I would like to draw attention to two issues.

Firstly, the authors refer to common measurement scales that are used in medicine. It is crucial to understand the limits of a measurement to begin to appreciate results from any study. They describe the continuous scale and offer blood pressure and temperature measurements as examples. This scale refers to data determined such that the distance between any two points is known and measureable. Siegel used the term "ratio scale" if there was a true zero point to the measurement.2 This contrasts to an ordinal categorical scale, in which the intervals are not constant. The scale referred to can be transformed, and is anchored with respect to the measurements to some reproducible point. The term "ratio" for this scale seems preferable, as the world is, in essence, discrete when measured, in the quantum sense. Certainly, the measured world is not continuous, at least as far as we can determine it.

Secondly, the authors do not mention resampling methods.3 These can be very powerful and are attractive in biomedical research when the distribution may not be defined. While I realise these methods are relatively new, they do seem unreasonably ignored in undergraduate medical education.