Hi,
I have a multilevel situation where subjects are nested within clinics, and
each subject has multiple measurements.
For simplicity, suppose there 4 clinics, 3 subjects per clinic, and each
subject has 3 repeated measures.
Outcome is continuous. I am trying to implement this model with lmer
function in lme4 library.
lmeobj1<-lmer(outcome~med+time+medtime+(time|clinid)+(subjid|clinid))
My data set is as follows: med has two levels, time has three levels,
medtime is the interaction between med and time, subjid is the id numbers
for subjects,
clinid is the id numbers for clinics. I pasted the data below.
The above code is giving the same results with fixed effects regression. In
addition, whatever I put as random effects
is not making a difference at all. What am I doing wrong?
>cbind(outcome,med,time,medtime,subjid,clinid)
outcome med time medtime subjid clinid
[1,] 0.8511317 0 0 0 10 4
[2,] 3.9524773 0 1 0 10 4
[3,] 2.1637332 0 2 0 10 4
[4,] 1.6713403 1 0 0 1 1
[5,] 1.7379582 1 1 1 1 1
[6,] 5.0951544 1 2 2 1 1
[7,] 0.9523377 1 0 0 2 1
[8,] 2.4599613 1 1 1 2 1
[9,] 5.1759744 1 2 2 2 1
[10,] -0.9495338 1 0 0 4 2
[11,] 2.9300264 1 1 1 4 2
[12,] 3.7025651 1 2 2 4 2
[13,] 1.1628554 1 0 0 6 2
[14,] 4.1536130 1 1 1 6 2
[15,] 5.0869188 1 2 2 6 2
[16,] 0.3114241 0 0 0 7 3
[17,] 0.6007636 0 1 0 7 3
[18,] 2.2783941 0 2 0 7 3
[19,] -0.7095164 0 0 0 8 3
[20,] -0.1541448 0 1 0 8 3
[21,] 1.6037837 0 2 0 8 3
[22,] 1.9994632 0 0 0 9 3
[23,] 0.8047261 0 1 0 9 3
[24,] 0.1828438 0 2 0 9 3
[25,] 2.7219649 0 0 0 12 4
[26,] 2.3046305 0 1 0 12 4
[27,] 1.1838549 0 2 0 12 4
[28,] 0.6292358 1 0 0 3 1
[29,] 2.9953366 1 1 1 3 1
[30,] 3.9291266 1 2 2 3 1
[31,] 0.8726671 0 0 0 11 4
[32,] -0.4657651 0 1 0 11 4
[33,] 3.0364098 0 2 0 11 4
[34,] 0.3046405 1 0 0 5 2
[35,] 0.8789185 1 1 1 5 2
[36,] 4.1729769 1 2 2 5 2
Thanks,
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