[R-sig-ME] Why am I getting a Variance of 0 for my random effect
Daniel Ezra Johnson
danielezrajohnson at gmail.com
Wed Aug 11 20:16:24 CEST 2010
Try data1$RN <- as.factor(data1$RN).
On Wed, Aug 11, 2010 at 2:13 PM, Kevin E. Thorpe
<kevin.thorpe at utoronto.ca> wrote:
> 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.
>
>
> R version 2.11.1 Patched (2010-07-21 r52598)
> Copyright (C) 2010 The R Foundation for Statistical Computing
> ISBN 3-900051-07-0
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> Natural language support but running in an English locale
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> Type 'q()' to quit R.
>
>> 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
>
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