I have a dataset with about 500,000 subjects and I am trying to establish whether the variance is equal. I first performed an F-test but then I realised the data is slightly skewed with kurtosis. So then I went with the Brown-Forsythe variation of the Levene test of variance because it utilises the median and thus is less influenced by non-normality in the data. Then I realised that, due to the central limit theorem, if the sample is sufficiently large, then one can treat the data as normally distributed.
So now I am torn. Do I perform the F-test or the Levene's test? Or is there a better test to carry out on data this size?