[R-sig-ME] lme function to obtain pvalue for fixed effect

Thierry Onkelinx thierry.onkelinx at inbo.be
Tue May 26 22:09:49 CEST 2015


Because they test different hypothesis.

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

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

2015-05-26 21:46 GMT+02:00 li li <hannah.hlx op gmail.com>:

> Thanks so much for replying.
> Yes LimerTest package could be used to get pvalues when using lmer
> function. But still the summary and anova function give different
> pvalues.
>    Hanna
>
> 2015-05-26 15:19 GMT-04:00, byron vinueza <byronvinu_8 op hotmail.com>:
> > You can use the lmerTest package .
> >
> >
> >
> >
> >
> > Enviado desde mi iPhone
> >
> >> El 26/5/2015, a las 13:18, li li <hannah.hlx op gmail.com> escribió:
> >>
> >> Hi all,
> >>  I am using the lme function to run a random coefficient model. Please
> >> see
> >> output (mod1) as below.
> >>  I need to obtain the pvalue for the fixed effect. As you can see,
> >> the pvalues given using the summary function is different from the
> >> resutls given in anova function.
> >> Why should they be different and which one is the correct one to use?
> >>   Thanks!
> >>      Hanna
> >>
> >>
> >>> summary(mod1)
> >> Linear mixed-effects model fit by REML
> >> Data: minus20C1
> >>        AIC       BIC   logLik
> >>  -82.60042 -70.15763 49.30021
> >>
> >> Random effects:
> >> Formula: ~1 + months | lot
> >> Structure: General positive-definite, Log-Cholesky parametrization
> >>            StdDev       Corr
> >> (Intercept) 8.907584e-03 (Intr)
> >> months      6.039781e-05 -0.096
> >> Residual    4.471243e-02
> >>
> >> Fixed effects: ti ~ type * months
> >>                     Value   Std.Error DF   t-value p-value
> >> (Intercept)     0.25831245 0.016891587 31 15.292373  0.0000
> >> type             0.13502089 0.026676101  4  5.061493  0.0072
> >> months          0.00804790 0.001218941 31  6.602368  0.0000
> >> type:months -0.00693679 0.002981859 31 -2.326329  0.0267
> >> Correlation:
> >>               (Intr) typ months
> >> type        -0.633
> >> months         -0.785  0.497
> >> type:months  0.321 -0.762 -0.409
> >>
> >> Standardized Within-Group Residuals:
> >>          Min            Q1           Med            Q3           Max
> >> -2.162856e+00 -1.962972e-01 -2.771184e-05  3.749035e-01  2.088392e+00
> >>
> >> Number of Observations: 39
> >> Number of Groups: 6
> >>> anova(mod1)
> >>            numDF denDF   F-value p-value
> >> (Intercept)     1    31 2084.0265  <.0001
> >> type            1     4   10.8957  0.0299
> >> months          1    31   38.3462  <.0001
> >> type:months     1    31    5.4118  0.0267
> >>
> >> _______________________________________________
> >> R-sig-mixed-models op r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
>
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