Post #2154512

@emjonaitis procedures like the dbreg package (https://grantmcdermott.com/dbreg/) basically do the following: summarize the rows into buckets of profiles, and then perform weighted regression (weighted by how many people fall in each profile) This might be possible for you? Even though there are many rows there might be an order of magnitude fewer unique rows. You would need to bin your continuous predictors, so this is also approximate And not sure if this will even work with the nested structure