I’ve been struggling to get the concept behind random-effects meta-analysis out for some time – it’s the ‘average effectiveness’ in an ‘average population’ – with the prediction interval being the ‘actual width of where the truth might lie’.
But .. yes .. but what does that actually mean & why does that matter?
Take a primary school. Get the average height of the children in each class. Now use that to tell me the average height of a child in that school.
If I make a tonne of jogging pants for them based on the average height, I might provide 15% with an OK fit, but mostly they’ll be too long or too short.
If the data are very very heterogeneous, the average is “true”, it’s just not very useful.
Does that make any more sense of how awkward a ‘random effects meta-analysis’ result can be in a highly heterogenous meta-analysis?
(ps – The overall average height might be useful to order the right amount of material from the weavers shed though.)