I am using the package nlme to fit a simple random effects (variance
components model)

with 3 parameters:  overall mean (fixed effect), between subject
variance (random) and 

within subject variance (random).

 

I have 16 subjects with 1-4 obs per subject. 

 

I need a 3x3 variance-covariance matrix that includes all 3 parameters
in order to 

compute the variance of a specific linear combination.

 

But I can't get the 3x3 matrix.  Should I specify the formulae in lme

differently or is there some other suggestion that I might try?

 

Thank you very much for any advice.  my data and code follows.  

 

"mydata" <-

structure(list(subject = c(17, 17, 17, 17, 5, 16, 16, 8, 8, 8, 

8, 7, 7, 7, 7, 9, 9, 9, 10, 10, 11, 11, 11, 12, 12, 12, 12, 14, 

14, 14, 14, 15, 15, 15, 15, 13, 13, 13, 1, 1, 1, 2, 2, 2, 2, 

3, 3, 3, 4, 4, 4), y = c(-2.944, -5.521, -4.644, -4.736, -5.799, 

-4.635, -5.986, -5.011, -3.989, -4.682, -6.975, -6.064, -5.991, 

-8.068, -5.075, -5.298, -6.446, -5.037, -6.534, -4.828, -5.886, 

-4.025, -6.607, -5.914, -4.159, -6.757, -4.564, -5.011, -5.416, 

-5.371, -5.768, -7.962, -5.635, -4.575, -5.268, -6.975, -5.598, 

-7.669, -8.292, -7.265, -5.858, -7.003, -3.807, -5.829, -5.613, 

-3.135, -5.136, -5.394, -5.011, -5.598, -4.174)), .Names = c("subject", 

"y"), class = "data.frame", row.names = c("1", "2", "3", "4", 

"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 

"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", 

"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", 

"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", 

"49", "50", "51"))

 

lme.res<-lme(fixed=y~1,data=mydata,random=~1|subject,method="ML")

VarCorr(lme.res)

 


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