[R] extracting p-values from lmer outputs
Martin Maechler
maechler at stat.math.ethz.ch
Sat Mar 4 21:50:19 CET 2006
>>>>> "Lngmyers" == Lngmyers <lngmyers at ccu.edu.tw>
>>>>> on Sat, 04 Mar 2006 10:45:55 +0800 writes:
Lngmyers> Thanks to Martin Maechler for the helpful
Lngmyers> information below.
Lngmyers> I guess I didn't make myself clear enough. I had
Lngmyers> already discovered all them slots in lmer objects,
Lngmyers> but these are apparently mostly input things or
Lngmyers> things created in the course of the analysis, not
Lngmyers> the output itself -- that is, it still takes work
Lngmyers> to derive from them the text printed on the screen
Lngmyers> when lmer is used. I am a mere mortal, not a
Lngmyers> statistician.
Lngmyers> The output of anova(lmerout) (where "lmerout" is a
Lngmyers> lmer object) is an ordinary list, so the lines it
Lngmyers> prints are easy to access, but this is not true of
Lngmyers> lmerout itself. I didn't want anova(lmerout)
Lngmyers> because, as MM said, certain key values have been
Lngmyers> suppressed to avoid controversial.
Lngmyers> However, the version of lmer currently available
Lngmyers> on CRAN (lme4 0.995-2 2006-01-17 and Matrix
Lngmyers> 0.995-5 2006-02-07) still gives p-values for GLMM.
Lngmyers> I assumed that they weren't banned there because
Lngmyers> they're calculated using z values, making DF
Lngmyers> irrelevant. The datasets I'll be using always have
Lngmyers> over 600 observations, so z values should work
Lngmyers> fine.
that makes a lot of sense to me
Lngmyers> So two questions:
Lngmyers> (1) Are the fixed-effects p-values produced by
Lngmyers> lmer for GLMM still considered to be valid, or
Lngmyers> were they left in the last revision by mistake?
Lngmyers> Should I give up on these p-values and test for
Lngmyers> significance of each fixed effect by using
Lngmyers> anova(full-model, model-minus-one-of-the-fixed-effects)?
I'd think the P-values are all fine
but you (James) could try anyway and confirm that the anova()
results give +/- the same
Lngmyers> (2) Assuming the p-values given by lmer for GLMM
Lngmyers> are valid, is there any easy way to derive them
Lngmyers> from a lmer object? Thanks to MM's tip, I looked
Lngmyers> more closely and found the estimates for the fixed
Lngmyers> effects, but I don't see standard errors or z
Lngmyers> values. They must be readily calculable
"readily calculable" indeed: If you type
selectMethod("show", "lmer")
you see the function which is called when a "lmer" object is printed
{since S4 objects are printed by show(), not print() }.
When you start looking at it, you may reconsider the word "readily" :-)
Lngmyers> from what's in the lmer object, but I'm too ignorant to
Lngmyers> figure it out myself.
The current setup will be improved soon (within 2 weeks).
Doug Bates and I are currently improving the documentation of
lmer objects and the methods you can apply and also plan to make
summary(<lmer>) return a new object which contains many more
useful parts, typically those that you now see when the <lmer>
object is printed.
Martin Maechler, ETH Zurich
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