[R] extracting p-values from lmer outputs

[Lngmyers]

Thanks to Martin Maechler for the helpful information below.

I guess I didn't make myself clear enough. I had already discovered all
them slots in lmer objects, but these are apparently mostly input things
or things created in the course of the analysis, not the output itself
-- that is, it still takes work to derive from them the text printed on
the screen when lmer is used. I am a mere mortal, not a statistician.

The output of anova(lmerout) (where "lmerout" is a lmer object) is an
ordinary list, so the lines it prints are easy to access, but this is
not true of lmerout itself. I didn't want anova(lmerout) because, as MM
said, certain key values have been suppressed to avoid controversial.

However, the version of lmer currently available on CRAN (lme4 0.995-2
2006-01-17 and Matrix 0.995-5 2006-02-07) still gives p-values for GLMM.
I assumed that they weren't banned there because they're calculated
using z values, making DF irrelevant. The datasets I'll be using always
have over 600 observations, so z values should work fine.

So two questions:

(1) Are the fixed-effects p-values produced by lmer for GLMM still
considered to be valid, or were they left in the last revision by
mistake? Should I give up on these p-values and test for significance of
each fixed effect by using anova(full-model,
model-minus-one-of-the-fixed-effects)?

(2) Assuming the p-values given by lmer for GLMM are valid, is there any
easy way to derive them from a lmer object? Thanks to MM's tip, I looked
more closely and found the estimates for the fixed effects, but I don't
see standard errors or z values. They must be readily calculable from
what's in the lmer object, but I'm too ignorant to figure it out myself.

-- 
James Myers
Graduate Institute of Linguistics
National Chung Cheng University
168 University Road, Min-Hsiung
Chia-Yi 62102
TAIWAN
Email:  Lngmyers at ccu.edu.tw
Web:    http://www.ccunix.ccu.edu.tw/~lngmyers/
Phone:  886-5-242-8251
Fax:    886-5-272-1654

Martin Maechler wrote:
> 
> >>>>> "lngmyers" == lngmyers  <lngmyers at ccu.edu.tw>
> >>>>>     on Fri, 3 Mar 2006 21:54:52 +0800 (CST) writes:
> 
>     lngmyers> I would like to write a function that runs GLMM using lmer
>     lngmyers> on a user-input model containing interactions, but if the
>     lngmyers> model doesn't produce significant results for the interaction,
>     lngmyers> a reduced model will be run without the interaction.
>     lngmyers> Doing this seems to require getting the p-values out of an
>     lngmyers> lmer object, but I don't know how to do this. (The grand
>     lngmyers> DF debate seems to be irrelevant since the number of observations
>     lngmyers> for what I want to do with this will always be over 600 or so.)
>     lngmyers> The problem is that the output of lmer is a list of length 0.
>     lngmyers> My "brilliant" idea, shown below, is to divert the display to
>     lngmyers> a file, then read the file as a string. I guess it's useful
>     lngmyers> to save the full summary somewhere, but is there really
>     lngmyers> no more elegant way to do this?
> 
> I'm not answering your question directly,
> just the (implicit)
>        ``how can I extract parts from an 'lmer' object ? ''
> 
> If you used    str(lmerout)
> to inspect the STRucture of the lmerout object,
> you'd seen something like
> 
> > str(lmerout)
> Formal class 'lmer' [package "Matrix"] with 35 slots
>   ..@ assign  : int(0)
>   ..@ frame   :`data.frame':    180 obs. of  3 variables:
>   .. ..$ Reaction: num [1:180] 250 259 251 321 357 ...
>   .. ..$ Days    : num [1:180] 0 1 2 3 4 5 6 7 8 9 ...
>   .. ..$ Subject : Factor w/ 18 levels "308","309","310",..: 1 1 1 1 1 1 1 1 1 1 ...
> 
>   ............
>   ............
> 
> which tells you two things (and more) :
> 
> 1) you have an object of a *formal* class,
>    ``i.e.'' an S4 object
> 
> 2) you can (and typically will) use  " lmerout @ <slotname> "
>    to extract the slots of your lmerout result object.
> 
> Note that the above is a low-level / technical approach and you
> should rather work with the official documentation:
> 
>  ?lmer             points you to "lmer-class" and
> 
>  class ? lmer   or
>  ?lmer-class    {that one is needed for ESS}
> 
> contains a description of the "lmer" object and its (most
> important) slots.
> 
> Note BTW that in the most uptodate versions of  'lme4'/'Matrix'
> you won't get any P-values anymore directly
> {just because of the never-ending "DF war"}.
> 
> Martin Maechler, ETH Zurich
> 
>     lngmyers> - James Myers
>     lngmyers> National Chung Cheng University
>     lngmyers> Minhsiung Chiayi 621 Taiwan
> 
>     lngmyers> lmerout = lmer(Y ~ X1 * X2 + (1|Subj), data = dat, family = "binomial")
>     lngmyers> sink("lmerout.txt")
>     lngmyers> lmerout
>     lngmyers> sink()
>     lngmyers> lmerout.string = readChar("lmerout.txt",20000)
>     lngmyers> splitstring = strsplit(lmerout.string,"\r\n")
>     lngmyers> # If I counted right, the line with the interaction is [19]:
>     lngmyers> interstring = strsplit(splitstring[[1]][19]," ")
>     lngmyers> # Lines contain TABs, so the p-value is the eighth element along:
>     lngmyers> pvalue = as.numeric(interstring[[1]][8])
>     lngmyers> if(pvalue < .05) print("The interaction is significant!")
> 
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