Linear mixed model using R
1. Post on R-sig-mixed-models, not here. 2. Models 2 and 3 make no sense (to me, anyway). What do you think they mean? (Don't answer here -- explain on the mixed models list). -- Bert
On Thu, Aug 16, 2012 at 9:13 PM, li li <hannah.hlx at gmail.com> wrote:
Dear all, I am trying to use R to fit mixed models. Take the following example, where ind is a random effect and sample is fixed. I wanted to fit Model 1: values = ind + sample Model 2: values =ind * sample Model 3: values=ind(sample) + sample Tried to use the below for mod1, but it did not work.
Can anyone give
some help on this. Thanks so much.
mod1 <- lme(values ~ sample +
random=~ 1|ind, data=y)
Your syntax is wrong. Re-read ?lme (random is a separate argument, not part of the formula).
values ind sample
1 0.03325 1 1
2 0.03305 1 1
3 0.03185 1 1
4 0.03515 1 1
5 0.03375 1 1
6 0.01180 1 2
7 0.01850 1 3
8 0.02915 1 4
9 0.06200 1 5
10 0.03230 2 1
11 0.03345 2 1
12 0.03385 2 1
13 0.03605 2 1
14 0.03225 2 1
15 0.01145 2 2
16 0.01805 2 3
17 0.02950 2 4
18 0.05995 2 5
19 0.03425 3 1
20 0.03575 3 1
21 0.03535 3 1
22 0.03380 3 1
23 0.03410 3 1
24 0.01050 3 2
25 0.01735 3 3
26 0.03140 3 4
27 0.06170 3 5
28 0.03430 4 1
29 0.03185 4 1
30 0.03165 4 1
31 0.03380 4 1
32 0.03235 4 1
33 0.01100 4 2
34 0.01825 4 3
35 0.03045 4 4
36 0.06060 4 5
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Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm