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