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

[Ben Bolker]

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On 15-05-26 06:56 PM, li li wrote:
> You are right! Then I am not sure whether the test in ANOVA 
> corresponding to a continuous variable makes sense. Hanna
> 

   I'm not sure what you mean.

   summary() gives Wald (marginal) tests of individual parameters;
anova gives *sequential* F tests.  (They agree for the interaction
term.)   This is a large topic.  You might find car::Anova() to be a
useful tool for this ...

> 2015-05-26 16:09 GMT-04:00, Thierry Onkelinx
> <thierry.onkelinx at inbo.be>:
>> 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 at 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 at hotmail.com>:
>>>> You can use the lmerTest package .
>>>> 
>>>> 
>>>> 
>>>> 
>>>> 
>>>> Enviado desde mi iPhone
>>>> 
>>>>> El 26/5/2015, a las 13:18, li li <hannah.hlx at 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 at r-project.org mailing list 
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>> 
>>> 
>>> _______________________________________________ 
>>> R-sig-mixed-models at r-project.org mailing list 
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>> 
>> 
> 
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