Ummm...
Define: "Confidence interval for BLUP" .
I know what a confidence interval for a parameter or function of parameters
(which is what a predicted value is) is; but a BLUP is neither, so I don't
get what a confidence interval for it should mean.
Feel free to reply off list, as this is clearly not an R question.
Bert Gunter
Genentech Nonclinical Statistics
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
Behalf Of Rick Bilonick
Sent: Friday, November 09, 2007 9:47 AM
To: R Help
Subject: [R] Confidence Intervals for Random Effect BLUP's
I want to compute confidence intervals for the random effect estimates
for each subject. From checking on postings, this is what I cobbled
together using Orthodont data.frame as an example. There was some
discussion of how to properly access lmer slots and bVar, but I'm not
sure I understood. Is the approach shown below correct?
Rick B.
# Orthodont is from nlme (can't have both nlme and lme4 loaded at same
time!)
# OrthoFem<-Orthodont[Orthodont$Sex=="Female",]
# http://tolstoy.newcastle.edu.au/R/help/06/03/23758.html
library(lme4)
fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem)
lmer(distance~age+(age|Subject), data=OrthoFem)@bVar$Subject[2,2,]*
(attr(VarCorr(lmer(distance~age+(age|
Subject),data=OrthoFem)),"sc")^2)[1]
(attr(VarCorr(fm1OrthF.),"sc")^2)[1]
fm1.s <- coef(fm1OrthF.)$Subject
fm1.s.var <- fm1OrthF. at
bVar$Subject*(attr(VarCorr(fm1OrthF.),"sc")^2)[1]
fm1.s0.s <- sqrt(fm1.s.var[1,1,])
fm1.s0.a <- sqrt(fm1.s.var[2,2,])
fm1.s[,1]+outer(fm1.s0.s, c(-2,0,2))
fm1.s[,2]+outer(fm1.s0.a, c(-2,0,2))
> fm1.s
(Intercept) age
F10 14.48493 0.3758608
F09 17.26499 0.3529804
F06 16.77328 0.3986699
F01 16.95609 0.4041058
F05 18.36188 0.3855955
F07 17.28390 0.5193954
F02 16.05461 0.6336191
F08 19.40204 0.3562135
F03 16.35720 0.6727714
F04 19.02380 0.5258971
F11 19.13726 0.6498911
> fm1.s[,1]+outer(fm1.s0.s, c(-2,0,2))
[,1] [,2] [,3]
[1,] 12.21371 14.48493 16.75616
[2,] 14.99377 17.26499 19.53622
[3,] 14.50205 16.77328 19.04450
[4,] 14.68487 16.95609 19.22732
[5,] 16.09066 18.36188 20.63311
[6,] 15.01267 17.28390 19.55512
[7,] 13.78339 16.05461 18.32584
[8,] 17.13082 19.40204 21.67327
[9,] 14.08598 16.35720 18.62843
[10,] 16.75257 19.02380 21.29502
[11,] 16.86604 19.13726 21.40849
> fm1.s[,2]+outer(fm1.s0.a, c(-2,0,2))
[,1] [,2] [,3]
[1,] 0.1738325 0.3758608 0.5778890
[2,] 0.1509522 0.3529804 0.5550087
[3,] 0.1966417 0.3986699 0.6006982
[4,] 0.2020775 0.4041058 0.6061340
[5,] 0.1835672 0.3855955 0.5876237
[6,] 0.3173671 0.5193954 0.7214236
[7,] 0.4315909 0.6336191 0.8356474
[8,] 0.1541852 0.3562135 0.5582417
[9,] 0.4707432 0.6727714 0.8747997
[10,] 0.3238688 0.5258971 0.7279253
[11,] 0.4478629 0.6498911 0.8519194
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