Dear list users,

To begin, I apologise for any naivety displayed in this post! I'm still trying to come to terms with some of the ideas in spatial regression. I hope someone can provide me with some guidance on a problem I have.

I am analysing data on individuals nested within zones so automatically used multilevel modelling to reflect this hierarchy. I have both individual level and zone level variables to use to determine an individual level response. All zones are found within a city and some of the zones for which I have individual level information are neighbours. I have a matrix of 0s and 1s to reflect this information so I was wondering if it possible to fit some sort of spatial multilevel model to this data in R? I am not sure that this is necessary as it does not appear that the random slope effect for zones is significant in the model. However, I retained this effect as some of the zone level variables are statistically significantly associated with the response.

Is there some sort of a test to assess whether or not there is residual spatial autocorrelation which has not been taken into account by my multilevel model? I tried extracting the zone level residual information and using a moran test. However, I have a feeling that this may not be the correct approach to take. Anyone have any suggestions?

Cheers,
Karen
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