On 8/11/06, Simon Pickett <[EMAIL PROTECTED]> wrote:
> Hi,
> Thanks for your response, it nearly worked! But it only wrote one coloumn
> of data and not the three columns I need.
> Using fixef(m1) doesnt give the same results as coef(m1) when you are
> using more than one random effect. I need the coefficients for each
> individual so I use coef(m1) to get this which results in an object of
> class lmer.coef, 3 columns by 700 rows.
> as.data.frame() wont work on this and I cant seem to specify that I want
> three columns when I tried <-matrix(lmer.coef,ncol=length(lmer.coef))....
> Thanks very much,
Situations like this are when Martin Maechler's str function comes in
so handy. It displays the structure of the object from which you will
see that coef(lmerModel) returns a list of data frames, not a data
frame. You can create a matrix from an element of thiis list easily.
> library(Matrix)
Loading required package: lattice
> data(sleepstudy)
> (fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy))
Linear mixed-effects model fit by REML
Formula: Reaction ~ Days + (Days | Subject)
Data: sleepstudy
AIC BIC logLik MLdeviance REMLdeviance
1753.628 1769.593 -871.8141 1751.986 1743.628
Random effects:
Groups Name Variance Std.Dev. Corr
Subject (Intercept) 612.090 24.7405
Days 35.072 5.9221 0.066
Residual 654.941 25.5918
number of obs: 180, groups: Subject, 18
Fixed effects:
Estimate Std. Error t value
(Intercept) 251.4051 6.8246 36.838
Days 10.4673 1.5458 6.771
Correlation of Fixed Effects:
(Intr)
Days -0.138
> str(coef(fm1))
Formal class 'coef.lmer' [package "Matrix"] with 1 slots
..@ .Data:List of 1
.. ..$ :`data.frame': 18 obs. of 2 variables:
.. .. ..$ (Intercept): num [1:18] 254 211 212 275 274 ...
.. .. ..$ Days : num [1:18] 19.67 1.85 5.02 5.65 7.40 ...
> as.matrix(coef(fm1)[[1]])
(Intercept) Days
308 253.6637 19.6662580
309 211.0065 1.8475846
310 212.4448 5.0184079
330 275.0956 5.6529533
331 273.6653 7.3973901
332 260.4446 10.1951148
333 268.2455 10.2436606
334 244.1725 11.5418624
335 251.0714 -0.2848734
337 286.2955 19.0955683
349 226.1950 11.6407015
350 238.3351 17.0814918
351 255.9829 7.4520285
352 272.2687 14.0032983
369 254.6806 11.3395024
370 225.7922 15.2897520
371 252.2121 9.4791308
372 263.7196 11.7513151
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