How do I extract random effects for a particular group from an R lme object?

I have successfully fit a linear mixed-effects model, and I'm looking to extract the random effect component for individual groups. I know that the full list of random effects can be extracted using

random.effects(model)

Then print(random.effects(model)) gives a two-column list of group names and random effects, even though the data itself appears to have only on开发者_StackOverflowe column. My question is whether it is possible to "look up" the random effect associated with a particular group by the group name, or, if not, how I can find a list of group names in the same order as the random effects in the data frame that is output by random.effects().

Thanks

Mark Ch.

---

The problem, it turns out, was my particular way of indexing the groups. ranef(lme) returns a data frame where the row names are the group names. In my data, I used a very long number to differentiate between groups, which R rounded to a handful of decimal places. That meant it was impossible to exactly reference individual groups by name.

I solved the problem by converting every index to a base-62 number. I used digits and the lower and upper case alphabet as the set of characters in the number. (That is, the number matched [a-zA-Z0-9]*) This dramatically reduced the length of the group name and made it impossible for R to round the group name -- the more characters you use, the shorter it gets.

Now, if I do:

M3.ranef <- ranef(M3)
x <- M3.ranef[group_ID,1]

x is the random effect for the group named group_ID, which is how data frames are supposed to work.

---

Is this what you're looking for?

> library(nlme)    
> fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc),
            data = Loblolly,
            fixed = Asym + R0 + lrc ~ 1,
            random = Asym ~ 1,
            start = c(Asym = 103, R0 = -8.5, lrc = -3.3))

> str(random.effects(fm1))
Classes ‘ranef.lme’ and 'data.frame':   14 obs. of  1 variable:
 $ Asym: num  -5.57 -5.02 -1.69 -2.36 -2.98 ...
 - attr(*, "effectNames")= chr "Asym"
 - attr(*, "label")= chr "Random effects"
 - attr(*, "level")= int 1
 - attr(*, "standardized")= logi FALSE
 - attr(*, "grpNames")= chr "Seed"
> random.effects(fm1)$Asym
 [1] -5.5654676 -5.0168202 -1.6920794 -2.3587798 -2.9814647 -1.4018554
 [7] -0.1100587 -2.3613150  1.1947892  2.0119121  2.9862349  3.5890462
[13]  4.6094776  7.0963810

---

> library(nlme)
> d <- data.frame(x=rep(letters, each=5),
                z=rep(LETTERS[1:13], each=10),
                y=rep(rnorm(26, sd=2), each=5) + rep(rnorm(13), each=10) + rnorm(26 * 5))
> r <- ranef(d)   # random.effects is a synonym for this
# Look at the structure of r
> str(r)
List of 2
 $ z:'data.frame':  13 obs. of  1 variable:
  ..$ (Intercept): num [1:13] -1.575 -0.365 -1.817 0.235 2.369 ...
  ..- attr(*, "effectNames")= chr "(Intercept)"
 $ x:'data.frame':  26 obs. of  1 variable:
  ..$ (Intercept): num [1:26] -0.8628 0.0536 1.724 -1.9115 -1.1764 ...
  ..- attr(*, "effectNames")= chr "(Intercept)"
 - attr(*, "label")= chr "Random effects"
 - attr(*, "level")= int 2
 - attr(*, "standardized")= logi FALSE
 - attr(*, "grpNames")= chr [1:2] "z" "x %in% z"
 - attr(*, "class")= chr [1:2] "ranef.lme" "list"
> head(r$x)
    (Intercept)
A/a -0.86283867
A/b  0.05360748
B/c  1.72401850
B/d -1.91145501
C/e -1.17643222
C/f  0.24315559
> head(r$z)
  (Intercept)
A  -1.5752441
B  -0.3648627
C  -1.8167101
D   0.2353324
E   2.3685118
F  -1.7544619
> r$z["A", ]
[1] -1.575244
> r$x["A/a", ]
[1] -0.8628387