 
Summary: An aspect of discrete data analysis: tting a
betabinomial distribution to the hospitals data
P.M.E.Altham, Statistical Laboratory, University of Cambridge
January 30, 2002
Address Centre for the Mathematical Sciences, Wilberforce Road, Cam
bridge CB3 OWB, UK, Fax no 01223337956.
P.Altham@statslab.cam.ac.uk
I was an invited speaker at the meeting
`The Design and Analysis of Potency Assays for Biotechnology Products'
at the National Institute for Biological Standards and Control, UK, October
56, 2000.
Keywords Overdispersion, betabinomial, SPlus, glm.
Abstract
Statistical analysis for discrete data, particularly for probability models such as
the binomial, Poisson and multinomial, is by now very well understood, with a
wealth of suitable software. It can happen that the standard glm (generalized
linear modelling) software is not completely appropriate, since overdispersion
is present, relative to the standard distributions such as the Poisson or the
binomial. Failure to take account of this overdispersion, for example in tting
a model such as log(p=(1 p)) = + x (where the covariate x is the dose)
