Two Wrongs

Dichotomisation Destroys Data

Dichotomisation Destroys Data

Sometimes we categorise continuous data rather sloppily. For example, it’s common to judge the scope of tasks to be “small”, “medium”, or “large” rather than the actual time estimated. Any conclusions we draw from categorised data are greatly affected by this practise, but we rarely look at exactly what the effects are before we choose to categorise. There’s a brief paper that looks into the prevalence of this practise and gives some (common-sense) recommendations around the practise1 Categorisation of continuous risk factors in epidemiological publications; Turner, Dobson, & Pocock; Epidemiological Perspectives & Innovations; 2010. Available online..

And, perhaps the one that was most surprising to me: