Description Usage Format Examples

Simulated data set for illustrating shrinkage.

1 |

A data frame with 200 observations on the following 6 variables.

`intercept`

a numeric vector for the intercept.

`frequency`

a numeric vector for word frequency.

`subject`

a factor for subjects with levels

`S1`

,`S2`

, ... ,`S10`

.`error`

a numeric vector for residuals.

`ranef`

a numeric vector for random effect.

`RT`

a numeric vector for simulated RTs.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | ```
## Not run:
data(shrinkage)
require(lme4)
require(lmerTest)
require(optimx)
shrinkage.lmer = lmer(RT ~ frequency + (1|subject),
data = shrinkage,
control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb"))
shrinkage.lmList = lmList(RT ~ frequency | subject, data = shrinkage)
# and visualize the difference between random regression
# and mixed-effects regression
mixed = coef(shrinkage.lmer)[[1]]
random = coef(shrinkage.lmList)
subj = unique(shrinkage[,c("subject", "ranef")])
subj = subj[order(subj$subject),]
subj$random = random[,1]
subj$mixed = mixed[,1]
subj = subj[order(subj$random),]
subj$rank = 1:nrow(subj)
par(mfrow=c(1,2))
plot(subj$rank, subj$random, xlab="rank", ylab="RT", ylim=c(200,550), type="n")
text(subj$rank, subj$random, as.character(subj$subject), cex=0.8, col="red")
mtext("random regression", 3, 1)
points(subj$rank, 400+subj$ranef, col="blue")
abline(h=400)
plot(subj$rank, subj$mixed, xlab="rank", ylab="RT", ylim=c(200,550), type="n")
text(subj$rank, subj$mixed, as.character(subj$subject), cex=0.8, col = "red")
mtext("mixed-effects regression", 3, 1)
points(subj$rank, 400+subj$ranef, col="blue")
abline(h=400)
par(mfrow=c(1,1))
## End(Not run)
``` |

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