Hi,

Some time ago, I was pointed to use the kinship package to include the 
variance/co-variance in a mixed model. My code is as follows and works well 
(it does not give any error).

>     aa <- lmekin(dta1[,j] ~ dta1[,k] + g1:g2:g3:g4,data = dta1, random = ~ 
1|geno, varlist = list(K), subset = Year==i)
> aa
Linear mixed-effects kinship model fit by maximum likelihood
  Data: dta1 
  Subset: Year == i 
  Log-likelihood = -581.048 
  n= 192 

Fixed effects: dta1[, j] ~ dta1[, k] + g1:g2:g3:g4 
                Estimate  Std. Error    t value      Pr(>|t|)
(Intercept)   80.5622757    1.468117 54.8745492 1.185858e-117
dta1[, k]1    -0.5091199    1.448478 -0.3514860  7.256174e-01
dta1[, k]na   -7.8414997    2.202464 -3.5603297  4.691413e-04
g1:g2:g3:g4 -657.2792180 1337.706920 -0.4913477  6.237537e-01

Wald test of fixed effects =  18.29943 df =  3 p =  0.0003815272

Random effects: ~1 | geno 
 Variance list: list(K) 
                   geno     resid
Standard Dev: 3.2863076 3.8496073
% Variance:   0.4215502 0.5784498


Now I would like to calculate the significance of dta[,k]. The anova function 
does not work on objects of class lmekin. Any help will be very much 
appreciated.

Marc.

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