When I use a model fit with LME, I get an error if I try to use "predict" with
a dataset consisting of a single line.
For example, using this data:
> simpledata
Y t D ID
1 -1.464740870 1 0 1
2 1.222911373 2 0 1
3 -0.605996798 3 0 1
4 0.155692707 4 0 1
5 3.849619772 1 0 2
6 4.289213902 2 0 2
7 2.369407737 3 0 2
8 2.249052533 4 0 2
9 0.920044316 1 0 3
10 2.003262622 2 0 3
11 0.003833438 3 0 3
12 1.578300927 4 0 3
13 -0.842322442 1 1 4
14 -0.657256158 2 1 4
15 1.504491575 3 1 4
16 2.896007045 4 1 4
17 0.990505440 1 1 5
18 2.722942793 2 1 5
19 4.395861278 3 1 5
20 4.849296475 4 1 5
21 3.049616421 1 1 6
22 2.874405962 2 1 6
23 4.359511097 3 1 6
24 6.165419699 4 1 6
This happened:
> testLME <- lme(Y~t+D,data=simpledata,random=~1|ID)
> predict(testLME, simpledata[1,])
Error in val[revOrder, level + 1] : incorrect number of dimensions
This has occurred with other datasets as well. Is this a bug in the code, or
am I doing something wrong?
(Also, is there a way to parse a formula of a type given to "random"? For
example, given ~1+t|ID, I'd like to be able to extract all the variable names
to the left of | and to the right of |, the way one can with a normal formula.)
Thanks in advance!
Rebecca
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