Why am I getting a Variance of 0 for my random effect

Hello.

I'm getting a variance of 0 on a random effect and I don't know why.
I suspect I've not set the model up correctly. ?My transcript is below
with my own comments sprinkled in for time to time.

A little bit about the data (which I will provide off-list if requested).
?We have nurses managing an aspect of patient care
according to different algorithms. ?Interest focuses on of the
algorithms result in different outcomes. ?I have restricted this
to only nurses who did each algorithm twice (in case my problem
was being caused by some nurses doing only one algorithm, possibly
only one time).

I figured that since I have multiple observations per nurse, I
should treat nurse as a random effect, but maybe I confused myself
again.


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library(lattice)
library(lme4)

str(data1)

'data.frame': ? 72 obs. of ?3 variables:
?$ RN ? ? ? ?: int ?1 1 2 3 7 7 9 9 15 15 ...
?$ Assignment: Factor w/ 2 levels "E","N": 1 1 1 1 1 1 1 1 1 1 ...
?$ AUChr ? ? : num ?12.26 7.23 9.26 4.04 10.31 ...

tmp1 <- with(data1,aggregate(AUChr,list(RN=RN,Assigment=Assignment),mean))
names(tmp1)[3] <- "Mean"

tmp2 <- with(data1,aggregate(AUChr,list(RN=RN,Assignment=Assignment),var))
names(tmp2)[3] <- "Variance"

meanvar <- merge(tmp1,tmp2)

The point of this is to show that the means are not all the same,
nor are the variances.

meanvar

? RN Assignment ? Mean ?Variance
1 ? 1 ? ? ? ? ?E ?9.745 ?12.65045
2 ? 1 ? ? ? ? ?N ?7.185 ? 1.36125
3 ?15 ? ? ? ? ?E 10.605 ?15.07005
4 ?15 ? ? ? ? ?N 10.385 ? 4.41045
5 ?16 ? ? ? ? ?E ?8.175 ? 0.00845
6 ?16 ? ? ? ? ?N ?8.420 ? 1.03680
7 ? 2 ? ? ? ? ?E ?7.300 ? 7.68320
8 ? 2 ? ? ? ? ?N ?6.950 ? 1.00820
9 ?21 ? ? ? ? ?E ?9.670 ? 9.41780
10 21 ? ? ? ? ?N 10.535 ? 2.44205
11 22 ? ? ? ? ?E ?7.720 ? 2.04020
12 22 ? ? ? ? ?N ?7.930 ? 1.21680
13 24 ? ? ? ? ?E ?9.555 ?10.35125
14 24 ? ? ? ? ?N ?9.330 ? 0.38720
15 25 ? ? ? ? ?E ?8.240 ? 0.92480
16 25 ? ? ? ? ?N ?9.485 ? 0.00125
17 27 ? ? ? ? ?E ?8.635 ? 0.08405
18 27 ? ? ? ? ?N ?7.745 ? 3.72645
19 28 ? ? ? ? ?E ?9.635 ? 8.61125
20 28 ? ? ? ? ?N ?8.315 ?10.35125
21 ?3 ? ? ? ? ?E ?6.005 ? 7.72245
22 ?3 ? ? ? ? ?N 11.435 ?55.44045
23 31 ? ? ? ? ?E ?9.590 ? 9.94580
24 31 ? ? ? ? ?N 10.570 ?16.70420
25 35 ? ? ? ? ?E ?9.055 ? 0.32805
26 35 ? ? ? ? ?N ?9.925 ?14.41845
27 36 ? ? ? ? ?E ?9.040 ? 2.08080
28 36 ? ? ? ? ?N ?7.395 ? 1.14005
29 ?5 ? ? ? ? ?E ?8.430 ? 3.38000
30 ?5 ? ? ? ? ?N 17.385 139.94645
31 ?6 ? ? ? ? ?E ?6.930 ? 0.24500
32 ?6 ? ? ? ? ?N ?8.330 ? 1.72980
33 ?7 ? ? ? ? ?E 10.650 ? 0.23120
34 ?7 ? ? ? ? ?N ?7.375 ? 0.09245
35 ?9 ? ? ? ? ?E ?8.885 ? 7.56605
36 ?9 ? ? ? ? ?N ?8.405 ? 0.73205

Model with "Assignment" (algorithm).

lmer(AUChr~Assignment+(1|RN),data=data1,REML=FALSE)

Linear mixed model fit by maximum likelihood
Formula: AUChr ~ Assignment + (1 | RN)
? Data: data1
? AIC ? BIC logLik deviance REMLdev
?365.7 374.8 -178.8 ? ?357.7 ? 356.9
Random effects:
?Groups ? Name ? ? ? ?Variance Std.Dev.
?RN ? ? ? (Intercept) 0.0000 ? 0.0000
?Residual ? ? ? ? ? ? 8.4152 ? 2.9009
Number of obs: 72, groups: RN, 18

Fixed effects:
? ? ? ? ? ?Estimate Std. Error t value
(Intercept) ? 8.7703 ? ? 0.4835 ? 18.14
AssignmentN ? 0.5131 ? ? 0.6837 ? ?0.75

Correlation of Fixed Effects:
? ? ? ? ? ?(Intr)
AssignmentN -0.707


Model without the algorithm variable.

lmer(AUChr~(1|RN),data=data1,REML=FALSE)

Linear mixed model fit by maximum likelihood
Formula: AUChr ~ (1 | RN)
? Data: data1
? AIC ? BIC logLik deviance REMLdev
?364.3 371.1 -179.1 ? ?358.3 ? 358.5
Random effects:
?Groups ? Name ? ? ? ?Variance Std.Dev.
?RN ? ? ? (Intercept) 0.000 ? ?0.0000
?Residual ? ? ? ? ? ? 8.481 ? ?2.9122
Number of obs: 72, groups: RN, 18

Fixed effects:
? ? ? ? ? ?Estimate Std. Error t value
(Intercept) ? 9.0268 ? ? 0.3432 ? ?26.3

sessionInfo()

R version 2.11.1 Patched (2010-07-21 r52598)
Platform: i686-pc-linux-gnu (32-bit)

locale:
?[1] LC_CTYPE=en_US ? ? ? LC_NUMERIC=C ? ? ? ? LC_TIME=en_US
?[4] LC_COLLATE=C ? ? ? ? LC_MONETARY=C ? ? ? ?LC_MESSAGES=en_US
?[7] LC_PAPER=en_US ? ? ? LC_NAME=C ? ? ? ? ? ?LC_ADDRESS=C
[10] LC_TELEPHONE=C ? ? ? LC_MEASUREMENT=en_US LC_IDENTIFICATION=C

attached base packages:
[1] stats ? ? graphics ?grDevices utils ? ? datasets ?methods ? base

other attached packages:
[1] lme4_0.999375-34 ? Matrix_0.999375-42 lattice_0.18-8

loaded via a namespace (and not attached):
[1] grid_2.11.1 ? nlme_3.1-96 ? stats4_2.11.1

proc.time()

? user ?system elapsed
?3.488 ? 0.056 ? 3.536

--
Kevin E. Thorpe
Biostatistician/Trialist, Knowledge Translation Program
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.thorpe at utoronto.ca ?Tel: 416.864.5776 ?Fax: 416.864.3016