How are you?

 

A simple question, theoretically, has a simple answer. That's not necessarily the case in a clinical trial, though. To measure in a way that can detect differences between groups, researchers often have to use methods that bear no relationship to how we think of a problem, or usually describe it.

Pain is a classic example. We use a lot of vivid words to try to explain our pain. But in a typical health study, that will be standardized. If that were done with what's called a "dichotomous" outcome – a straight up "yes or no" type question – it can be easy to understand the result.

But outcomes like pain can be measured on a scale, which is a "continuous" outcome: how bad is that pain, from nothing to the worst you can imagine? By the time average results between groups of people's scores get compared, it can be hard to translate back into something that makes sense. That's what the woman in the cartoon here is doing: comparing herself to people on a scale.

It pays to never put too much weight on the name of an outcome – check what it really means in the context of that study. There could be fine print that would make a difference to you – for example, “mortality” is measured, but only in the short-term, and you might have to dig hard to figure that our. Or the name the outcome is given might not be what it sounds like at all. People use the same names for outcomes they measure very differently.

Even something that sounds cut and dried can be...complicated. “Perinatal mortality” – death around childbirth – starts and ends at different times before and after birth, from country to country. “Stroke” might mean any kind, or some kinds. And then there's the complexity of composite outcomes – where multiple outcomes are combined and treated as if they're a single one. More on that here at Statistically Funny.

Some researchers put in the hard work of interpreting study measures to make sense in human terms. It would help the rest of us if more of them did that!

More posts on outcomes at Statistically Funny

And what's a standard deviation from the mean?

This post is based on a section of a post on deciphering outcomes in clinical trials at my Absolutely Maybe blog.

Hilda Bastian