I have the following case. My data set consists of 78 policy documents (= my observations). These were written by 50 different country governments (in the period between 2005 and 2020). While 27 countries have written only one policy document, 23 countries have written multiple policy documents. In the latter case, these same-country different-policy documents have usually been written years apart by different governments/administrations and different ministries. Nevertheless, I reckon there is probably a risk that the observations are not independent. My overarching question is, therefore: How would you calculate correlations in this case? More specifically:

1. Pearson assumes the independence of the observations, thus, is not suitable here, correct? Or could one even credibly argue that the observations are independent after all, since they were usually published many years (and therefore governments) apart and by different ministries?

2. Would "within-participants correlation" (Bland & Altman 1995 a & b) or "repeated measures correlation" (= RMCORR in R and Stata) be more suitable? Or is something else more appropriate?

3. Furthermore: Would I otherwise have to take into account any time effects when running correlations in my setting?

Thank you very much for your advice!

Disclaimer: also posted at Statalist here.