lmer output format for random effects misleading

[MarcKery]

Dear developers,

I find lme4 a great software, but I think that part of the output format is confusing to downright wrong. Here is part of the output from fitting a simple random-intercepts model:

Linear mixed model fit by REML ['lmerMod']
Formula: mass ~ length + (1 | pop)
....
Random effects:
Groups Name Variance Std.Dev.
pop (Intercept) 362.9 19.05
Residual 1810.6 42.55
Number of obs: 560, groups: pop, 56

Fixed effects:
Estimate Std. Error t value
(Intercept) 231.330 3.117 74.22
length 60.730 1.873 32.43

I have two and a half problems with this:
(1) The heading "Random effects" is basically wrong: it implies that there come the estimates of the random effects in the model. Instead, we get the variance and the std of the random effects and of the residuals. There is nothing random about these parameters: they are fixed effects just as much as are the intercept and the slope of length in the table headed "Fixed effects". A better, though perhaps too long, title for this table might be "Random effects dispersion parameters". The header "Fixed effects" is also misleading (though not wrong), because it implies that the variance params are not fixed effects. Hence, a different header for it might also be appropriate, though I can't come up with some good suggestion here.
(2) Also in the "Random effects" table, while the wording strictly is correct, it is potentially misleading to have a Std.Dev.: in almost all model fitting output in R that I have seen, the column to the right of a point estimate contains the SE of the estimate. This is also the case for the "Fixed effects" part of the table. So, I wouldn't be surprised if many people mistakenly thought that what is under 'Std.Dev.' is the SE of the variance parameter. Perhaps one could change the names of these two cols to 'Variance scale' and 'SD scale' ? Again longer, but in my opinion much less inviting for a misunderstanding.

In view of the tremendous confusion that still surrounds mixed models for many non-statisticians, I'd suggest using as precise language as possible.

Best regards -- Marc