08 August 2019 4 6K Report

I'm trying to figure out the most appropriate way of modelling repeated observations. In my case I have 5 annual observations of 20 brands in 10 product categories, and some sources suggest a mixed effects model, say in SPSS, in which you specify the type of correlation between each observation .... and then other sources suggest clustering the errors ... despite lots of reading, I can't quite figure which approach is most appropriate. Then an added complexity is some brands (like retailer's brands) are present in more than one product category which means I would ideally accomodate the dependence across observations at two levels (?). Any advice gratefully appreciated.

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