How to read a paper: Statistics for the non-statistician. I: Different types of data need different statistical tests
- 9 August 1997
- Vol. 315 (7104) , 364-366
- https://doi.org/10.1136/bmj.315.7104.364
Abstract
As medicine leans increasingly on mathematics no clinician can afford to leave the statistical aspects of a paper to the “experts.” If you are numerate, try the “Basic Statistics for Clinicians” series in the Canadian Medical Association Journal 1 2 3 4 or a more mainstream statistical textbook.5 If, on the other hand, you find statistics impossibly difficult, this article and the next in this series give a checklist of preliminary questions to help you appraise the statistical validity of a paper. ### Have they determined whether their groups are comparable, and, if necessary, adjusted for baseline differences? Most comparative clinical trials include either a table or a paragraph in the text showing the baseline characteristics of the groups being studied. Such a table should show that the intervention and control groups are similar in terms of age and sex distribution and key prognostic variables (such as the average size of a cancerous lump). Important differences in these characteristics, even if due to chance, can pose a challenge to your interpretation of results. In this situation, adjustments can be made to allow for these differences and hence strengthen the argument.6 #### Summary points In assessing the choice of statistical tests in a paper, first consider whether groups were analysed for their comparability at baseline Does the test chosen reflect the type of data analysed (parametric or non-parametric, paired or unpaired)? Has a two tailed test been performed whenever the effect of an intervention could conceivably be a negative one? Have the data been analysed according to the original study protocol? If obscure tests have been used, do the authors justify their choice and provide a reference? ### What sort of data have they got, and have they used appropriate statistical tests? Numbers are often used to label the properties of things. We can assign a number to represent our height, weight, and so on. For properties like these, the measurements can be treated as actual numbers. We can, for example, calculate the …Keywords
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