Dear R Community,
My data have 3 conditions and each condition has 6 replicates. I am trying to
fit my data for a linear mixed model using the lmer function from lme4 package
to find the random effects of the replicates; however, I got the error message.
Here are the example codes:
>example.3=data.frame(levels=as.numeric(XXX[,c(4)]),replicate=rep(c("0","1","2","3","4","5"),3),conditions=c(rep("11",6),rep("12",6),rep("13",6)))>
> example.3 levels replicate conditions1 43.1111 0 112
>42.0942 1 113 57.8131 2 114 57.1726
>3 115 77.8678 4 116 44.7578 5 117
>69.5078 0 128 52.0581 1 129 40.0602
>2 1210 45.5487 3 1211 43.6201 4 1212
>60.4939 5 1213 64.1932 0 1314 53.4055
>1 1315 59.6701 2 1316 52.6922 3 1317
>53.8712 4 1318 60.2770 5 13>
>m.example.3=lmer(as.numeric(levels)~conditions+(conditions|replicate),data=example.3)Error:
> number of observations (=18) <= number of random effects (=18) for term
>(conditions | replicate); the random-effects parameters and the residual
>variance (or scale parameter) are probably unidentifiable>
Could anyone help me figure out how to fix the issue?
Thank you very much for any inputs!
Ace
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