Hi all,
I am unsure about whether I need to adjust for multiple testing (i.e. changing to 99% confidence intervals) in my logistic regression models.
I am unsure what ‘counts’ as multiple testing. I have many logistic regression models (around 10) each on different slices of data - I don’t think that in itself counts as multiple testing?
Within each model - is it the total number of variables that counts as multiple testing?
Or is it the number of ‘levels’ within a category (e.g. age split up into 5 categories) and the number of comparisons you make between them?
Just to give you an idea of my models. This is one of them, and I have about 10 of these (they are individual models in their own right looking at different slices of the data so i don’t compare the models with each other). I am primarily looking at the impact of life events (financial and social events in the below example) on depression outcome whilst CONTROLLING for all other variables in the model i.e. I am just interested in how the estimates of the life events change when all the variables are included in the model.
Thank you!!
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