Dear Roger,

What do you mean by using correlation= argument to lme() to fit a model 
including within-group correlations? 

I tried it like this:
model3.fit <- lme(y ~ x3+x5+x7+x9+LnBankt500+Perceelkwaliteit+LnNS_Afstand+PGebouwd+LogoBedrijf+Bouwjaar_cat4+LnBanIndDistr500, random = ~1|GebID ,correlation=argument, datashab, method = "REML")

But this does not seem to work. What is the reason that nobody developed a moran's I for an lme object?




-----Oorspronkelijk bericht-----
Van: Roger Bivand [mailto:Roger.Bivand@nhh.no]
Verzonden: vr 6-8-2010 15:30
Aan: Sabira el Messlaki
Onderwerp: Re: your mail
 
On Fri, 6 Aug 2010, Sabira el Messlaki wrote:

>
> Dear Roger,

> How do I test the Moran's I in residuals of an lme object. I have done a 
> multilevel analysis and now I want to know if there is still spatial 
> autocorrelation.

Briefly, you have the opportunty to develop a test from the ground up 
yourself, as there are only tests for linear model residuals available. If 
you want to try to use a regular Moran's I on the residuals data frame 
columns from the fitted model, the significance tests will most likely be 
wrong.

Could you try using the correlation= argument to lme() to fit a model 
including within-group correlations, typically based on inter-observation 
distance? If the fit of lme() with and without this argument is the same, 
it would suggest that there is no residual within-group autocorrelation 
for your correlation scheme.

Hope this helps,

Roger

>
> Thank you in advance
>
> Sabira
>

-- 
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand@nhh.no




	[[alternative HTML version deleted]]

