My data has three factors, a discrete response and an offset column.>From the summary of a glm object derived using three way interactions,I get this deviance information: (Dispersion parameter for poisson family taken to be 1) Null deviance: 39244 on 896 degrees of freedom Residual deviance: 11913 on 795 degrees of freedom AIC: 13905 Number of Fisher Scoring iterations: 6 The rather high residual deviance could indicate that the data does not fit a poisson distrubution very well. That's believable since in quite a number of combinations of the three factors, zero occurs more often that one might expect for a Poisson distribution. Are there suggestions as to what might be a better way to analyse this data? Thanks -- ************************************************************* ___ Patrick Connolly {~._.~} HortResearch Great minds discuss ideas; _( Y )_ Mt Albert Average minds discuss events; (:_~*~_:) Auckland Small minds discuss people. (_)-(_) New Zealand .... Anon Ph: +64-9 815 4200 x 7188 ************************************************************* ______________________________________________________ The contents of this e-mail are privileged and/or confidential to the named recipient and are not to be used by any other person and/or organisation. If you have received this e-mail in error, please notify the sender and delete all material pertaining to this e-mail. ______________________________________________________ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On Fri, 25 Jan 2002, Patrick Connolly wrote:> > My data has three factors, a discrete response and an offset column. > >From the summary of a glm object derived using three way interactions, > I get this deviance information: > > (Dispersion parameter for poisson family taken to be 1) > > Null deviance: 39244 on 896 degrees of freedom > Residual deviance: 11913 on 795 degrees of freedom > AIC: 13905 > > Number of Fisher Scoring iterations: 6 > > > The rather high residual deviance could indicate that the data does > not fit a poisson distrubution very well. That's believable since in > quite a number of combinations of the three factors, zero occurs more > often that one might expect for a Poisson distribution. > > > Are there suggestions as to what might be a better way to analyse this > data?I would at least try a negative binomial (glm.nb in MASS), but as that seems to be a very large degree of over-dispersion it might not fit much better. You could fairly easily write code for a zero-augmented Poisson (a mixture of a Poisson and always zero) by a direct likelihood maximization. -- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._