[Statistical results: which method of presentation to chose?]

Hypothesis testing and significance is currently the most widely used method in the medical literature to report statistical results. However, this method has several limitations. The main one is linked to the risk of misinterpretation of the p value. The arbitrariness of the 5 percent value used to determine whether a result is or not statistically significant is not always kept in mind, and the concept of statistical significance might therefore be confused with that of clinical or biological relevance. The misinterpretation pitfalls are mostly linked to the fact that the p value does not give precise indications on the strength of the association and its direction, or on the variability in the sample. Therefore, some experts claim that hypothesis testing and significance should be avoided in reporting statistical results, and that the method based upon estimation and confidence interval should be more widely used. By this latter method, it is possible to know the direction of the association and the effect size (i.e. the strength of the association). The precision of the estimation, i.e. the variability of the estimation in the sample, can be assessed by the width of the confidence interval: the narrower the confidence interval, the more precise the estimation. Therefore, the clinical relevance of the findings is easier to infere from such results than from those only reporting p values. However, the estimation and confidence interval method is not without its own limitations. This method is difficult to apply to non-parametric tests, and for some results, such as the comparison of mortality ratios, the p value is highly informative. On the other hand, the misinterpretation risk is not totally ruled out when estimation and confidence interval method is used. In the situations where both methods can be employed, there is not yet in the scientific community a definite consensus on which method is the best one to report statistical results, hence some experts suggest that both methods can be presented simultaneously, especially for clinical and epidemiological studies.