## StatsMiniBlog: Propensity scores

Propensity scores are used mainly in observational studies assessing treatments as a way of balancing out measured variations in who received a treatment and who didn’t. In most observational studies, there are things which will have pushed the doc into prescribing the medicine in question, or the surgeon to take the knife to that patient […]

## StatsMiniBlog: Type I and II errors

After reading the title, most people now feel vaguely nauseous. If you throw in alpha and beta, or worse α and β, then there’s a distinctly bilious taste. Don’t get sick, though. Take a deep breath and fall back on what you already know: […]

## StatsMiniBlog: Bland Altman Plots

Measuring things is what we do lots of, and we often want to measure things with a new machine. New, faster, shinier, cheaper, less invasive or more colourful … but we are almost always sold it as being highly correlated with the reference standard (p<0.001). Think – what is this correlation and p-value telling us? […]

## StatsMiniBlog. Regression

Now, regression is a bad thing if we’re talking development. It might be any number of really difficult to pronounce neurological conditions, or severe psychological trauma, or abuse/neglect. It’s not going to be good. In statistics, it’s not quite the same. Regression is quite often a good thing. But what is it? […]

## StatsMiniBlog: Exact vs. approximate

You may well come across descriptions in the stats parts of papers that describe how the authors have derived their confidence intervals using an exact method. Sounds very good, doesn’t it? Precise to the most precicestness. And yet … sometimes an approximate confidence interval is better. You see, it all means what ‘exact’ exactly refers […]

## StatsMiniBlog: Subgroup or sensitivity analyses?

Perhaps becoming a little obscure, but there are some folk in the world who become concerned about undertaking analysis in systematic reviews. Some of these are described as “subgroup” analysis, others “sensitivity”. What’s the difference, and why? […]

## StatsMiniBlog: Odds and Probabilities

There’s something that is frequently wittered about but the odds are you’ve never really been bothered enough to care if there’s a difference between ‘probability’ and ‘odds’ (like relative risk and odds ratios). There are great reasons for this. Coffee, beer, ‘Take Me Out’ or a crash call to labour ward are four, for example. […]

## Sensitivity and specificity

Sensitivity and specificity are those sorts of things that can really get knickers twisted up something rotten. They sound like something you should be able to understand, they get used as if you understand them, and then you realise … it’s not quite as you thought …   Really diseased  Really not diseased    Test […]

## Positive about predictions

In a previous post I muttered about how unhelpful sensitivity and specificity are to practicing clinicians, and how what we really want to know are the predictive values of a test. Remembering the Table       Really diseased Really not diseased Test +ve A B 1.. A/(A+B) Test -ve C D 2.. C/(C+D) 5.. […]

## Gambling, alcohol and division.

No, not an average afternoon at the Houses of Parliament, but another in our diagnostics series. Moving yourself from looking at the predictive values of the tests as evaluated, to taking this information but using it in the situation you face, is a case of Bayesian mathematics. Which sounds hard. But its absolutely what you […]