  In many academic settings, medical students start their scientific work
already during their studies. Like at our institution, they often work in
interdisciplinary teams with more or less experienced (postgraduate)
researchers of pharmaceutical sciences, natural sciences in general, or
biostatistics. All of them should be taught good research practices as an
integral part of their education, especially in terms of statistical analysis.
This includes reproducibility as a central aspect of modern research.
Acknowledging that even educators might be unfamiliar with necessary aspects of
a perfectly reproducible workflow, I agreed to give a lecture series on
reproducible research (RR) for medical students and postgraduate pharmacists
involved in several areas of clinical research. Thus, I designed a piloting
lecture series to highlight definitions of RR, reasons for RR, potential merits
of RR, and ways to work accordingly. In trying to actually reproduce a
published analysis, I encountered several practical obstacles. In this article,
I focus on this working example to emphasize the manifold facets of RR, to
provide possible explanations and solutions, and argue that harmonized
curricula for (quantitative) clinical researchers should include RR principles.
I therefore hope these experiences are helpful to raise awareness among
educators and students. RR working habits are not only beneficial for ourselves
or our students, but also for other researchers within an institution, for
scientific partners, for the scientific community, and eventually for the
public profiting from research findings.
