Hi Karen

I am interested in this points too. What variable are you modeling? Counts
or incidence? did you standardized by population areas?

R has lot of spatial models for spatial models. see at
http://r-spatial.sourceforge.net/

hope this help

ivan

2009/11/26 Karen Lamb <k.lamb@sphsu.mrc.ac.uk>

> Hi,
>
> I am currently trying to determine a way of assessing whether or not there
> is spatial autocorrelation present in my model residuals and was hoping
> someone could help me with this.
>
> I have information on counts in over six thousand areas, with around half
> of the areas found to have  a count of zero. I decided to fit a
> Zero-Inflated Poisson model and a Negative Binomial as the data is greatly
> overdispersed. However, neither of these approaches take into account the
> likelihood that there is spatial autocorrelation present in the data set.
>
> I have been searching for the last two weeks to find appropriate methods to
> fit a spatial glm model. However, as I am new to spatial statistical
> methodology I am finding it difficult to decide how best to do this. It am
> not sure that any of the existing R functions are particularly suitable to
> my use. I am not interested in prediction as I have data on a population. I
> am interested in assessing the coefficients of variables and whether or not
> the variables are significant in determining outcome. I have noticed that a
> lot of analyses use a Bayesian approach which may be the way forward.
>
> My question, however, relates to the glm models I have fitted. I have
> included variables which may explain some of the spatial correlations such
> as urban/rural classification. I would like to see if any residual spatial
> autocorrelation remains in the model but cannot find a way of doing this. On
> searching the R-sig-Geo archives the Morans Test or Morans I are mentioned.
> However, I noticed someone had queried using the moran test in R for
> residuals from a logistic regression and had been told that lm.morantest()
> is available for linear regression but there is not an alternative for the
> glm. Has anyone got any suggestions for how to check my residuals? Are there
> particular plots that can be assessed?
>
> Thanks for your assistance.
>
> Cheers,
> Karen
>
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>



-- 
Luis Iván Ortiz Valencia
Estatístico Msc.
Spatial Analyst Msc.
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