Often, the data structure used in modelling is relatively straightforward - one subject per row. In contrast, I am analysing service accessibility in a country and each region represents a row in data.
I have medical service offer data by county (total of 14) and year (total of 7). I need to report year and local population-adjusted estimates.
offer ~ year + population + (1 | county)
Would it be correct to use the following data format for such modelling?
Or is this a problem that every county has multiple rows in data? I have an option to prepare my data in different ways, for example, also by month. Preparing data in different ways gives me different number of rows, possibly leading to narrower confidence intervals. What other biases such data manipulations may cause? What is a good practice here?