[R] anova(lme.model)

["Sibylle Stöckli"]

Dear R users

Topic: Linear effect model fitting using the nlme package (recomended by Pinheiro et al. 2008 for unbalanced data set).

The R help provides much info about the controversy to use the anova(lme.model) function to present numerator df and F values. Additionally different p-values calculated by lme and anova are reported. However, I come across the same problem, and I would very much appreciate some R help to fit an anova function to get similar p-values compared to the lme function and additionally to provide corresponding F-values. I tried to use contrasts and to deal with the ‚unbalanced data set’.

Thanks
Sibylle

> Kaltenborn<-read.table("Kaltenborn_YEARS.txt", na.strings="*", header=TRUE)
> 
> 
> library(nlme)

> model5c<-lme(asin(sqrt(PropMortality))~Diversity+ Management+Species+Height+Height*Diversity, data=Kaltenborn, random=~1|Plot/SubPlot, na.action=na.omit, weights=varPower(form=~Diversity), subset=Kaltenborn$ADDspecies!=1, method="ML")

> summary(model5c)
Linear mixed-effects model fit by maximum likelihood
 Data: Kaltenborn 
  Subset: Kaltenborn$ADDspecies != 1 
        AIC       BIC   logLik
  -249.3509 -205.4723 137.6755

Random effects:
 Formula: ~1 | Plot
        (Intercept)
StdDev:  0.06162279

 Formula: ~1 | SubPlot %in% Plot
        (Intercept)   Residual
StdDev:  0.03942785 0.05946185

Variance function:
 Structure: Power of variance covariate
 Formula: ~Diversity 
 Parameter estimates:
    power 
0.7302087 
Fixed effects: asin(sqrt(PropMortality)) ~ Diversity + Management + Species +      Height + Height * Diversity 
                      Value  Std.Error  DF   t-value p-value
(Intercept)       0.5422893 0.05923691 163  9.154585  0.0000
Diversity        -0.0734688 0.02333159  14 -3.148896  0.0071
Managementm+      0.0217734 0.02283375  30  0.953562  0.3479
Managementu      -0.0557160 0.02286694  30 -2.436532  0.0210
SpeciesPab       -0.2058763 0.02763737 163 -7.449198  0.0000
SpeciesPm         0.0308005 0.02827782 163  1.089210  0.2777
SpeciesQp         0.0968051 0.02689327 163  3.599602  0.0004
Height           -0.0017579 0.00031667 163 -5.551251  0.0000
Diversity:Height  0.0005122 0.00014443 163  3.546270  0.0005
 Correlation: 
                 (Intr) Dvrsty Mngmn+ Mngmnt SpcsPb SpcsPm SpcsQp Height
Diversity        -0.867                                                 
Managementm+     -0.173 -0.019                                          
Managementu      -0.206  0.005  0.499                                   
SpeciesPab       -0.253  0.085  0.000  0.035                            
SpeciesPm        -0.239  0.058  0.001  0.064  0.521                     
SpeciesQp        -0.250  0.041 -0.001  0.032  0.502  0.506              
Height           -0.518  0.532 -0.037 -0.004  0.038  0.004  0.033       
Diversity:Height  0.492 -0.581  0.031 -0.008 -0.149 -0.099 -0.069 -0.904

Standardized Within-Group Residuals:
        Min          Q1         Med          Q3         Max 
-2.99290873 -0.60522612 -0.05756772  0.62163049  2.80811502 

Number of Observations: 216
Number of Groups: 
             Plot SubPlot %in% Plot 
               16                48 

> anova(model5c)
                 numDF denDF   F-value p-value
(Intercept)          1   163 244.67887  <.0001
Diversity            1    14   1.53025  0.2364
Management           2    30   6.01972  0.0063
Species              3   163  51.86699  <.0001
Height               1   163  30.08090  <.0001
Diversity:Height     1   163  12.57603  0.0005
>

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