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problem with using R nlme function
2 messages · Zhiwei Tang, Ben Bolker
On 06/29/2011 11:57 AM, Zhiwei Tang wrote:
Dear R users, I am trying to converting a piece of my SAS code into R code, and I have met some difficulties which I couldn't figure out. The SAS code looks like this: proc mixed CL method=ml data = wholedata covtest; class site year tissue species fish_id; model fishSe = waterSe / outp=predict solution; random intercept / sub=site; repeated tissue/ sub=fish_id type=cs; run; Basically, I am trying to fit a random intercept linear mixed model to allow each *site *to have a different intercept and I also want to specify a variance-covariance structure (CS for example) within each *fish (fish_id) . *I do not know how can I fit this model with correct R code. I tried *lme* function included in the *nlme *package, with R code: lme(fixed=y~x,random=~1|site,correlation = corCompSymm(form = ~1|fishid), na.action=na.omit, method="REML") but R gave me error message like this: Incompatible formulas for groups in "random" and "correlation" I heard I can use the *nlme* function to have both the random and correlation statements together. I wonder how can I write the correct syntax to fit my model under *nlme *? I really have no clue about that.... I will be highly appreciated if anyone can give me any advice on this issue. Thank you in advance!
I believe you're required to have the correlation structured within the same units as the overall random effect, so lme(fixed=y~x,random=~1|site/fishid, correlation = corCompSymm(form =~1|site/fishid), na.action=na.omit, method="REML") But: doesn't compound symmetry at the fishid level mean the correlation statement would then be redundant? I don't quite understand the distinction between "random" and "repeated" in the SAS code (sorry ...) Ben Bolker