Hi everyone,
This is related to an earlier post. I'm studying repair time (in days) for vehicles which is a discrete count. I'm trying to remember the justification for including random effects? I'm considering repair state and vehicle make as random effects in a model amongst other variables. I imagine that each state and make has there own correlated responses. I have 2.8 million rows and 55 distinct makes. I heard that if the test set does not see a make that is in the training set then it will use the global mean for that observation. This sounds appealing, so I'm drawn towards this random effect idea. Any thoughts are appreciated.
Thanks.
This is related to an earlier post. I'm studying repair time (in days) for vehicles which is a discrete count. I'm trying to remember the justification for including random effects? I'm considering repair state and vehicle make as random effects in a model amongst other variables. I imagine that each state and make has there own correlated responses. I have 2.8 million rows and 55 distinct makes. I heard that if the test set does not see a make that is in the training set then it will use the global mean for that observation. This sounds appealing, so I'm drawn towards this random effect idea. Any thoughts are appreciated.
Thanks.