[R-sig-eco] How do I interpret linear mixed model contrast estimates from multcomp::glht()?

[Matthew Van Scoyoc]

​As I was suspecting, the answer is in contrast::contrast(). I'm going to
take this over to r-sig-mixed-models since that mailing list might be more
appropriate than ecology.​ Thanks Thierry, I appreciate the help.

Cheers

MVS
=====
Matthew Van Scoyoc

<mvanscoyoc at aggiemail.usu.edu>https://sites.google.com/site/scoyoc/
=====
Think SNOW!

On Fri, Dec 12, 2014 at 1:44 AM, ONKELINX, Thierry <Thierry.ONKELINX at inbo.be
> wrote:

> Dear Matthew,
>
> The part before "== 0" are the rownames of the matrix passed to linfct.
> When the rownames are missing, the rownumbers are used.
>
> Best regards,
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> + 32 2 525 02 51
> + 32 54 43 61 85
> Thierry.Onkelinx at inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
>
> -----Oorspronkelijk bericht-----
> Van: R-sig-ecology [mailto:r-sig-ecology-bounces at r-project.org] Namens
> Matthew Van Scoyoc
> Verzonden: vrijdag 12 december 2014 0:08
> Aan: r-sig-ecology at r-project.org
> Onderwerp: [R-sig-eco] How do I interpret linear mixed model contrast
> estimates from multcomp::glht()?
>
> So, what do the rows correspond to in the summary (e.g. "1 == 0")? I was
> thinking the answer was buried *cc*, but I can't figure it out. Consider
> this modified example I stole from here <
> https://stat.ethz.ch/pipermail/r-sig-mixed-models/2009q4/003061.html>...
>
> > options(contrasts = c(factor = "contr.SAS", ordered = "contr.poly"))
> > library("mlmRev")
> > library("lme4")
> > library("lmerTest")
> > library("contrast")
> > library("multcomp")
> >
> > data("egsingle")
> > # Linear mixed model
> > math.lmm <- lmer(math ~ year * size + female + (1|childid) +
> (1|schoolid), egsingle)
> > # Linear model
> > math.lm <- lm(math ~ year * size + female, data = egsingle) #
> > Calculate contrast matrix cc<-contrast(math.lm, a = list(year = c(.5,
> > 1.5, 2.5), size = 380, female
> = levels(egsingle$female)), +
>                                                 b = list(year = c(.5, 1.5,
> 2.5), size = 800, female = levels(egsingle$female)))
> > # Calculate estimates
> > summary(glht(math.lmm, linfct = cc$X))
>
>  Simultaneous Tests for General Linear Hypotheses
>
> Fit: lme4::lmer(formula = math ~ year * size + female + (1 | childid) +
>     (1 | schoolid), data = egsingle)
>
> Linear Hypotheses:
>               Estimate   Std. Error   z value   Pr(>|z|)
> 1 == 0  0.12774    0.08020     1.593     0.1272
> 2 == 0  0.15322    0.08066     1.900    0.0669 .
> 3 == 0  0.17870    0.08178     2.185    0.0341 *
> 4 == 0  0.12774    0.08020     1.593    0.1273
> 5 == 0  0.15322    0.08066     1.900    0.0669 .
> 6 == 0  0.17870    0.08178     2.185    0.0342 *
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Adjusted p
> values reported -- single-step method)
>
> Ultimately I would like to create a dataframe so I can plot the contrasts,
> something like this...
>
> > x = summary(glht(math.lmm, linfct = cc$X)) # Contrast data frame
> > math.contr = data.frame(Effect.Interaction = ..., Estimate =
> x[["test"]]$coefficients, Std.Error = x[["test"]]$sigma)
>
> Thanks for the help!
> Cheers,
> MVS
> =====
> Matthew Van Scoyoc
>
> <
> https://mail.google.com/mail/?view=cm&fs=1&tf=1&to=mvanscoyoc@aggiemail.usu.edu
> >
> https://sites.google.com/site/scoyoc/
> =====
> Think SNOW!
>
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