The joy of having many data points

Researchers and clinicians are drawn to studies with many participants. Especially randomised controlled trials, where two groups are randomly divided and one gets “the real thing” while the other does not. The joy comes from knowing that results from these kinds of studies suggest that, all things being equal, the differences between the groups is “real” and not just by chance. When we come to analyse the graphs from these kinds of studies, what we hope to see are two nice bell-shaped curves, with distinct peaks (the arithmetic mean) and long tails either side – and a clear separation between the mean of one group (the experimental one) and the control group. It should look a bit like this: Now one of the problems in doing research is that we can’t always guarantee a large sample – for example, it’s difficult to find enough people with a relatively rare problem like complex regional pain syndrome to randomly split the groups to iron out major differences between them. And, this kind of research design presumes the principle of ergodicity – here for more information from Wikipedia, or here for a more detailed examination relating to generalising from groups to individuals. This research design also struggles to deal with distributions that don’t conform to the lovely bell curve – things like bimodal distributions, or skewed distributions. And if we draw only on the mean – we don’t g...
Source: HealthSkills Weblog - Category: Anesthesiology Authors: Tags: Assessment Occupational therapy Physiotherapy Professional topics Psychology Research Science in practice Uncategorized Chronic pain Clinical reasoning Health pain management Therapeutic approaches Source Type: blogs