Hi JAmes,
I'm afraid I've never used the packages so I'm no expert. But in answer to your questions..
1. Kulldorf recommends a fract pop of 0.5 but I guess if you have a reason to believe there is a different upper limit then you could compare results. Remember, this is the fraction of the total population, not the population of cases 2. Never used the opgam command..3. I think the kulldorf command in SpatialEpi package can detect more than 1 cluster..
Good luck!
> From: ROONEYJ4@tcd.ie
> To: r-sig-geo@r-project.org
> Date: Mon, 26 Aug 2013 22:23:26 +0100
> Subject: Re: [R-sig-Geo] output data from R to SaTScan
> 
> Hi Hugh,
> 
> Thanks for your answer. Yes I've seen it said that those packages can do most of what SaTScan does.
> I'm playing with Kulldorff's Statistic as implemented in section 11.5.6 of ASDAR - but a few things confuse me:
> 
> 1. How do I decide what the correct value for fractpop is ? I initially had it set to .25 and I was getting cluster of 50% of my cases which made no sense.
> 2. Is there any correction for multiple testing in the opgam() command ? I have over 3000 areas - do I need to set a very low alpha ?
> 3. How do I detect more than one cluster ? I have maps where I suspect 2 or 3 separate clusters based on smoothed RR's.
> 
> 
> My code currently looks like this (which I based on the code for Fig11.18 in the book and this useful question and answer: http://r-sig-geo.2731867.n2.nabble.com/Strange-results-in-DCluster-package-td7326832.html )
> 
> sa<-data.frame(Observed=ED$var1)
> sa<-cbind(sa, Expected=mean(ED$var1))
> sa<-cbind(sa, x=ED$x, y=ED$y)
> sa$Observed<-as.numeric(sa$Observed)
> 
> #Kuldorff-Nagarwalla analysis
> mle<-calculate.mle(sa, model="poisson") 
> knres<-opgam(data=sa, thegrid=sa[,c("x", "y")], alpha=.025, R=99,
>              iscluster=kn.iscluster, fractpop=.10, model="poisson", mle=mle, log.v=TRUE)
> 
> #Print cluster result
> clusters<-get.knclusters(as(ED, "data.frame"), knres)
> i<-which.max(knres$statistic)
> 
> ED$KNcluster<-""
> ED$KNcluster[clusters[[i]]]<-"cluster"
> ED$KNcluster[clusters[[i]][1]]<-"centre"
> ED$KNcluster<-as.factor(ED$KNcluster)
> 
> print(spplot(ED, "KNcluster", main="Kulldorff's method",
>               col.regions=c(gray(1), gray(.5), gray(.8))))
> 
> 
> Thanks,
> James
> 
> 
> ________________________________________
> From: Hugh Sturrock [hughsturrock@hotmail.com]
> Sent: 26 August 2013 17:10
> To: James Rooney; r-sig-geo@r-project.org
> Subject: RE: [R-sig-Geo] output data from R to SaTScan
> 
> Hi James,
> 
> Not sure how to do that, but check out SpatialEpi and Dcluster packages, I believe they can do a lot of what SaTScan does..
> 
> Cheers, Hugh
> 
> > From: ROONEYJ4@tcd.ie
> > To: r-sig-geo@r-project.org
> > Date: Mon, 26 Aug 2013 16:42:55 +0100
> > Subject: [R-sig-Geo] output data from R to SaTScan
> >
> > Hi all,
> >
> > So I have created some maps in R, smoothed then using the BYM model in Openbugs and opened the CODA files in R once again to analyze results etc.
> >
> > I would like to now test for clusters using SaTScan and the post smoothing data - but I can find very little info anywhere on how to output my R data into a format that SaTScan can use. My data within R is in the form of a SpatialPolygonsDataFrame which up until now I have been saving as an ESRI shapefile with the command:
> > writeOGR(data, "", layer="data_out",driver="ESRI Shapefile",overwrite=T)
> >
> > But from what info I can find, I think this doesn't seem to be a useful format for SaTScan.
> >
> > Any advice would be appreciated on how to achieve this!
> > Many thanks,
> > James
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> 
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