[R] summary.lme and anova question

[Christoph Scherber]

Dear all,

Thanks to Brian Ripley for pointing this out. If I understand it correctly, this would mean that 
looking at the parameter estimates, standard errors and P-values in summary.lme only makes sense if 
no interaction terms are present?

My conclusion would then be that it is better to rely on the anova.lme() output when assessing the 
significance of terms in the model (rather than looking at the P-values from summary.lme).

Is that correct? Because in most books (e.g. Crawley, "The R book"), the P values from summary.lme 
are used to assess the significance of terms.

Best wishes,
Christoph












Prof Brian Ripley schrieb:
> Please read the help for anova.lme, and note the 'type' argument.  You 
> are comparing apples and oranges here (exactly as if you did this for a 
> linear model fit).
> 
> Because you have a three-way interaction in your model, looking at the 
> (marginal) t-tests for any other coefficient than the third-order 
> interaction violates the marginality principle.  And the third-order 
> interaction seems to be important.
> 
> On Thu, 21 Aug 2008, Christoph Scherber wrote:
> 
>> Dear all,
>>
>> When analyzing data from a climate change experiment using linear 
>> mixed-effects models, I recently
>> came across a situation where:
>>
>> - the summary(model) showed a significant difference between the 
>> levels of a two-level factor,
>> - while the anova(model) showed no significance for that factor (see 
>> below).
>>
>> My question now is: Is the anova.lme() approach correct for that 
>> model? And why does the F-test for CO2 yield a non-significant 
>> P-value, while the t-test in the summary.lme() is significant?
> 
> CO2 on its own explains little, but allowing different CO2 effects 
> within the levels of DROUGHT seems important.
> 
> A good book on fitiing linear models (e.g. MASS chapter 6) will explain 
> this to you.
> 
>> Many thanks for your help!
>>
>> Best wishes
>> Christoph
>>
>> ######################################################
>>
>> mod11=lme(log(ind1+1) ~ CO2*DROUGHT*TEMP, 
>> random=~1|B/C,na.action=na.exclude)
>>
>> summary(mod11)
>> Linear mixed-effects model fit by REML
>> Data: NULL
>>     AIC      BIC    logLik
>> 97.3077 115.6069 -37.65385
>>
>> Random effects:
>> Formula: ~1 | B
>>        (Intercept)
>> StdDev: 1.303146e-05
>>
>> Formula: ~1 | C %in% B
>>       (Intercept)  Residual
>> StdDev:   0.2466839 0.4846578
>>
>> Fixed effects: log(ind1 + 1) ~ CO2 * DROUGHT * TEMP
>>                     Value Std.Error DF   t-value p-value
>> (Intercept)       1.9981490 0.2220158 29  9.000030  0.0000
>> CO2              -1.0308687 0.3139778  5 -3.283254  0.0219
>> DROUGHT          -0.9715216 0.2798173 29 -3.471986  0.0016
>> TEMP             -0.5592615 0.2954130 29 -1.893151  0.0684
>> CO2:DROUGHT       1.2196261 0.3957214 29  3.082032  0.0045
>> CO2:TEMP          0.9791044 0.4068987 29  2.406261  0.0227
>> DROUGHT:TEMP      0.6413038 0.4068987 29  1.576077  0.1259
>> CO2:DROUGHT:TEMP -1.1448624 0.5675932 29 -2.017047  0.0530
>> Correlation:
>>                (Intr) CO2    DROUGHT TEMP   CO2:DROUGHT CO2:TE DROUGHT:
>> CO2              -0.707 DROUGHT          -0.630 
>> 0.446                                          TEMP -0.597  0.422  
>> 0.474                    CO2:DROUGHT       0.446 -0.630 -0.707 
>> -0.335                           CO2:TEMP          0.433 -0.613 -0.344 
>> -0.726  0.486                    DROUGHT:TEMP      0.433 -0.306 -0.688 
>> -0.726  0.486       0.527        CO2:DROUGHT:TEMP -0.311  0.439  0.493 
>> 0.520 -0.697 -0.717 -0.717
>> Standardized Within-Group Residuals:
>>      Min         Q1        Med         Q3        Max
>> -1.4631313 -0.5715171 -0.2024273  0.4592221  1.9568914
>>
>> Number of Observations: 47
>> Number of Groups:
>>      B C %in% B
>>      6       12
>>
>> ######################################################
>>
>> anova(mod11)
>>                numDF denDF   F-value p-value
>> (Intercept)          1    29 162.95719  <.0001
>> CO2                  1     5   1.15108  0.3324
>> DROUGHT              1    29   5.53240  0.0257
>> TEMP                 1    29   0.04519  0.8331
>> CO2:DROUGHT          1    29   5.66686  0.0241
>> CO2:TEMP             1    29   1.88455  0.1803
>> DROUGHT:TEMP         1    29   0.03481  0.8533
>> CO2:DROUGHT:TEMP     1    29   4.06848  0.0530
>>
>>
>> ######################################################
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide 
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 

-- 
Dr. rer.nat. Christoph Scherber
University of Goettingen
DNPW, Agroecology
Waldweg 26
D-37073 Goettingen
Germany

phone +49 (0)551 39 8807
fax   +49 (0)551 39 8806

Homepage http://www.gwdg.de/~cscherb1