In reply to Rolf Turner and Jean Adams who have been helping me:
This does appear to be an issue with NA values in the non-factor variables. In
the (non-reproducible) example below, we can see that removing the NAs solves
the problem. However, from what I can see to this point, there does not seem be
be rhyme nor reason to why the issue is taking place. A slight modification to
Rolf Turner's code (introducing some NAs) shows that, in general, NAs are not a
problem for lmer (indeed, it just runs na.omit as default).
Examining which factors are affected by the removal of the NAs shows no
discernible pattern - no factors disappeared, none became "1" or anything of
this nature.I will be able to proceed just by performing the na.omit
beforehand, but it is curious.
Thanks for your help everyone (especially Rolf Turner and Jean Adams)!
mod1<-lmer(beta~expData+techVar$RIN+techVar$sample_storage_time+(1|techVar$p_amplification))#Error:
(p <- ncol(X)) == ncol(Y) is not TRUE
mod1<-lm(beta~expData+techVar$RIN+techVar$sample_storage_time+techVar$p_amplification)#No
error given.
#trial with eliminating NAs elimSamps<-which(is.na(beta)) length(elimSamps)
#[1] 4
#eliminate the NAs from all vectors betaVals<-beta[-elimSamps]
expD<-expData[-elimSamps]) techRIN<-techVar$RIN[-elimSamps]
techTime<-techVar$sample_storage_time[-elimSamps]
techPlate<-factor(techVar$p_amplification[-elimSamps])
mod1<-lmer(betaVals~expD+techRIN+techTime+(1|techPlate))
summary(mod1)#Linear mixed model fit by REML ['lmerMod']#Formula: betaVals ~
expD + techRIN + techTime + (1 | techPlate)##REML criterion at convergence:
-1701.7##Scaled residuals:# Min 1Q Median 3Q Max#-2.3582
-0.6996 -0.1085 0.6079 4.6743##Random effects:# Groups Name
Variance Std.Dev.# techPlate (Intercept) 1.645e-05 0.004056# Residual
4.991e-03 0.070644#Number of obs: 709, groups: techPlate, 29##Fixed
effects:# Estimate Std. Error t value#(Intercept) 2.159e-01
9.871e-02 2.188#expD 2.330e-03 1.498e-02 0.156#techRIN
5.096e-03 4.185e-03 1.218#techTime 1.399e-06 1.565e-05
0.089##Correlation of Fixed Effects:# (Intr) expD tchRIN#expD
-0.919#techRIN -0.272 -0.103#techTime -0.206 0.063 0.021
summary(techPlate)# plate01 plate02 plate03 plate04 plate05 plate06
plate07 plate09# 1 22 34 28 31 28 32
10#plate09a plate10 plate11 plate13 plate14 plate15 plate16
plate17# 16 17 15 4 52 55 41
33# plate18 plate19 plate20 plate21 plate22 plate23 plate24 plate25#
50 42 21 50 13 22 17 7# plate26
plate27 plate28 plate30 plate32# 25 21 5 13 4
summary(techVar$p_amplification)# plate01 plate02 plate03 plate04 plate05
plate06 plate07 plate09# 1 22 34 28 31 28
32 10#plate09a plate10 plate11 plate13 plate14 plate15
plate16 plate17# 17 17 15 4 53 55 41
33# plate18 plate19 plate20 plate21 plate22 plate23 plate24
plate25# 50 42 21 50 13 22 17
8# plate26 plate27 plate28 plate30 plate32# 25 21 5
14 4
#Counter-example, where it functions fine#Example from Rolf Turner
set.seed(42)f <- factor(sample(1:29,713,TRUE))x <- seq(0,1,length=713)y <-
rnorm(713)require(lme4)
x[sample(1:713,4,replace=F)]<-NA
fit <- lmer(y ~ x + (1|f))#No error message given
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