The use of statistics in presenting results of research is common practice. Empirical studies are summarized using statistics and statistical methods based on samples of bigger populations are cost efficient. However, care needs to be exercised when interpreting results to guard against inappropriate conclusions derived from biased estimates. Since the topic has been highlighted and methods proposed to handle them, these methods were deemed worthy of a Nobel prize. The basic problem of a bias due to a selective sample has been demonstrated by Stockwell et al. (2024). The authors investigate the old question, whether a little bit of alcohol consumption (per day) could be beneficial for our health. The statistical issue which needs careful examination is the construction of the control group against which the results are compared. Apparently many studies have biased control groups which included persons in the not drinking control group who had stopped drinking for bad health previously. Compared to those persons with other health conditions those drinking a little bit compared rather well. But of course such individuals should not be present in a control group. Of the control group is biased due to many persons with below average health the groups of interest consuming higher levels of alcohol do not perform so badly. Hence, interpretation of results from medical or social science studies has to consider carefully the actual or potential sources of bias. Not really a new results in statistics, but still not well known or understood by the public at large. Drug consumption as well as studies of this consumption could deserve the same sticker: handle with care. (Image: Extract from Tenier II David, Les fumeurs, also entitled Chanson à boire, 17th century, Paris Petit Palais).
