I've been using poisson regression on aggregated data, using robust standard errors.
Having run a few models I decided to collapse the dataset further across a small number of variables I was not using in the models, and reran the same models. I was surprised that although the model coefficients stayed the same the robust standard errors changed. If I use the OIM standard errors they stay the same before and
after collapsing the data.
I'm unclear which robust standard errors I should use, and am concerned that they differ depending on
which variables I collapse by. Any advice would be extremely helpful.
Thanks
Carol Coupland
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Dr Carol Coupland
Division of Primary Care
School of Community Health Sciences
Floor 13, Tower Building,
University of Nottingham
Nottingham NG7 2RD
Tel: 0115 8466916 (or ext.66916)
Fax: 0115 8466904
email: [email protected]
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