[R] Equivalent of intervals() in lmer

[Dieter Menne]

Douglas Bates <bates <at> stat.wisc.edu> writes:

> If you want to examine the three means then you should fit the model as
> lmer(rcl ~ time - 1 + (1 | subj), fr)
> 

True, but for the notorious "error bars" in plots that reviewers always request
the 0.35 is probable more relevant than the 1.87. Which I think is justified in
this case, but in most non-orthogonal designs with three or more factors, where
we have a mixture of between/withing subject, there is no clear solution. What
to do when required to produce "error-bars" that reasonably mirror p-values? 

It's easier with British Journals  in the medical field that often have
statistical professionals as reviewers, but many American Journals with their
amateur physician/statisticians (why no t-test on raw data?) drive me nuts.

Dieter


#-------------
library(lme4)
recall <- c(10, 13, 13, 6, 8, 8, 11, 14, 14, 22, 23, 25, 16, 18, 20,  
15, 17, 17, 1, 1, 4, 12, 15, 17, 9, 12, 12, 8, 9, 12)
fr <- data.frame(rcl = recall, time = factor(rep(c(1, 2, 5), 10)),  
subj = factor(rep(1:10, each = 3)))
fr.lmer <- lmer(rcl ~ time -1 +(1 | subj), fr)
summary(fr.lmer)
fr.lmer <- lmer(rcl ~ time +(1 | subj), fr)
summary(fr.lmer)



------------------

Fixed effects:
      Estimate Std. Error t value
time1   11.000      1.879   5.853
time2   13.000      1.879   6.918
time5   14.200      1.879   7.556


Fixed effects:
            Estimate Std. Error t value
(Intercept)  11.0000     1.8793   5.853
time2         2.0000     0.3507   5.703
time5         3.2000     0.3507   9.125