Dear R-helper:
  I measured 40 different mouse strains. In 10 of them, I measured 2 males and 4 females for each strain. In another 10 of them, I measured 4 males and 2 females for each strain. In the remaining 20, I measured 3 males and 3 females for each strain. Totally, I have 240 data for 40 strains each of them have 6 data. 
  The model for the data can be written as, pheno=mu+sex+strain+e, where mu (mean) and sex (two levels) are fixed effects, and strain (40 levels) and e are random effects:
  result1 <- lme(pheno~sex, random=list(strain=~1),data=dat)     (model_1)
  This works and I obtained variances for both strain and residual. However, these 40 strains are highly correlated. I don't know to how to incorporate dependence among these strains into the above model. I already obtained a correlation matrix for the 40 strains. The below R does not work:
  result2 <- lme(pheno~sex, random=list(strain=~1), correlation=corSymm(value=c(0.8,0.7,...,0.4),form =~ Strain), data=dat)     (model_2)
   
  I will greatly appreciate if you can give some suggestions
   
   


Pengyuan Liu
Dept of Surgery
Washington Univ in St Louis
       
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