Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
From | Maarten buis <maartenbuis@yahoo.co.uk> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: ST: logistic regression and 'adequate numbers' |
Date | Wed, 6 Apr 2011 09:06:29 +0100 (BST) |
--- On Wed, 6/4/11, Ronald McDowell wrote: > I'm modelling the log odds of a > binary outcome as function of several covariates including > age. Unsurprisingly as my sample gets older I have fewer > numbers samppled for each year of age, and was wondering if > anyone had come across or used a 'rule of thumb' in terms of > how many sampled per age was 'too few' to include in the > model? I've read of studies restricted to certain ages > because of 'inadequate numbers' but haven't found a > definition of the latter. > > I'm aware I can perform sensitivity analysis, look at > residuals and the usual diagnostics (not all of which are > available in STATA in this case unfortunately), but if > anyone had any thoughts on the matter I'd be interested. There is a fairly complete set of types of residuals and other diagnostic tools after you estimate your model with -glm-. When it comes to age, I would not be worried about the number of observations but about selective mortality: people who survive to a very old age are different from the general population in many ways. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/