In many medical and social science studies, statistical data are used to support conclusions that may appear valid at first glance, yet upon deeper inspection, they may oversimplify complex realities or even mislead interpretation.

A recent Danish study on multiple sclerosis (MS) found no association between the number of clinic visits and mortality risk, while reporting that being female or married was linked to longer survival. This raises a critical methodological concern:

To what extent can statistical associations be misinterpreted as causal relationships? What safeguards should be in place to ensure that statistical analysis does not become a tool for drawing inaccurate or biased conclusions—especially in multifactorial contexts like chronic illness, where social and clinical factors intersect?

More Islam Abdullah El-Ghani Ghanem's questions See All
Similar questions and discussions