Dear list members,

 

I sampled a total of about 2000 leaves, nested in trees (10 per tree).
In the field, those trees are nested in 9 different provenances. On the
leaves, I measured some morphological parameters, for example 'length'.

Every provenance is characterised by some environmental factors, as for
example 'rainfall' and 'number of dry months'. These factors are the
same within avery provenance. Further, each tree is characterised by a
(arbitrary) degree of human pressure ('MG'). 

 

The objective of the study is to see in which way the environmental and
human factors are influencing leaf variables.

 

I constructed a linear mixed-effects model:

 

> lme1<-lme(lenght~MG+dry.months+rainfall, random=~1|provenance/tree)

 

I've chosen this random structure because of the field reality (leaves
are nested in trees, are nested in provenances).

 

Further, I constructed two other models with different random
structures:

> lme2<-update(lme1,random=~1|provenance)

> lme3<-update(lme1,random=~1|nr.boom)

 

When I compare these models with an anova, I have this output:

 

     Model df       AIC       BIC    logLik   Test  L.Ratio p-value

lme1     1  6 -3123.050 -3089.028 1567.5252                        

lme2     2  5 -1653.025 -1624.673  831.5125 1 vs 2 1472.025  <.0001

lme3     3  5 -2947.977 -2919.625 1478.9884                        

 

I have some questions about this output:

 

1)      Why are the logLik-values positive?

2)      I always heard: 'The smaller the logLik, the better the model'.
Is this also the case with positive logLik's? The residual errors of
model lme1 and lme3 are much smaller than the residual error of lme2, so
the 'tree'-effect is really important!

3)      The variables 'dry.months' and 'rainfall' are the same within
every provenance. What means this for the model?

  

Can anyone help me?

 

Thanks!!!

 

 

Sebastiaan De Smedt

Dept. Bioscience Engineering

University of Antwerp

Groenenborgerlaan 171-V616

B-2020 Antwerpen

T: +32 (0)3/265.35.17

F: +32 (0)3/265.32.25

 

 

P  Help to save paper - do you really need to print this e-mail???  P

 


	[[alternative HTML version deleted]]


