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Mixed models fixed effects

9 messages · Emma Stone, Simon Pickett, Mark Difford +1 more

Emma Stone
# 
Dear All,

This may sound like a dumb question but I am trying to use a mixed model to 
determine the predictors of bat activity along hedges within 8 sites. So my 
response is continuous (bat passes) my predictors fixed effects are 
continuous (height metres), width (metres) etc and the random effect is 
site  - can you tell me if the fixed effects can be continuous as all the 
examples I have read show them as categorical, but this is not covered in 
any documents I can find.

Help!

Emma
ONKELINX, Thierry
# 
Hi Emma,

Continuous predictors are no problem at all. You can mix both continuous
and categorial predictors if needed. I suppose your response are counts
(the number of bats that passes)? In that case a generalised linear
mixed model is more appropriate. With the lme4 package you could try
something like this:

library(lme4)
Model <- glmer(BatPasses ~ Width + Height + (1|Site), family = poisson)

HTH,

Thierry

PS There is a mailing list dedicated to mixed models: R-Sig-MixedModels
------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

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

-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Emma Stone
Verzonden: woensdag 11 maart 2009 15:29
Aan: r-help at r-project.org
Onderwerp: Re: [R] Mixed models fixed effects

Dear All,

This may sound like a dumb question but I am trying to use a mixed model
to 
determine the predictors of bat activity along hedges within 8 sites. So
my 
response is continuous (bat passes) my predictors fixed effects are 
continuous (height metres), width (metres) etc and the random effect is 
site  - can you tell me if the fixed effects can be continuous as all
the 
examples I have read show them as categorical, but this is not covered
in 
any documents I can find.

Help!

Emma

______________________________________________
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.

Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer 
en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document. The views expressed in  this message 
and any annex are purely those of the writer and may not be regarded as stating 
an official position of INBO, as long as the message is not confirmed by a duly 
signed document.
Simon Pickett
# 
Also check out these pdfs
http://cran.r-project.org/other-docs.html

and try to get your hands on the bible
http://www.amazon.co.uk/R-Book-Michael-J-Crawley/dp/0470510242

Simon.
Mark Difford
# 
Hi Simon,

Carefull, someone is likely to tell you that the "bible" is Pinheiro, J.C.,
and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer, and
that would be much closer to being correct. Others might mention something
by Searle. Nothing against Crawley, of course. But it usually is better to
get close to the source, and to the active researchers in the field. One
nice thing about the first reference (there are many others) is that Prof.
Bates is an active contributor to this list and to the SIG mixed-models list
(which he maintains):

https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

Check it out.

Regards, Mark.
Simon Pickett-4 wrote:

  
    

      
      
    

  


  


      

    

    
1 day later

    

      
      

        


  

        

      Emma Stone
    

    

      
      #
    

  


  

      
Hi Thierry,

That's great thanks!

I have done as you have said but I keep getting a warning message here is 
my code:

G1Hvol<-glmer(passes~hvolume+style+habitat(1|Site),family = poisson)

And this is the message i get:
Warning message:
In mer_finalize(ans) : false convergence (8)

any ideas??

Emma


--On 11 March 2009 15:45 +0100 "ONKELINX, Thierry"

        
<Thierry.ONKELINX at inbo.be> wrote:

        

            

      
      
      
    

        

      
      
    

        
----------------------
Emma Stone
Postgraduate Researcher
Bat Ecology and Bioacoustics Lab
& Mammal Research Unit
School of Biological Sciences,
University of Bristol, Woodland Road,
Bristol, BS8 1UG
Email: emma.stone at bristol.ac.uk

  
  


  


      

    

    

      
      

        


  

        

      ONKELINX, Thierry
    

    

      
      #
    

  


  

      
Dear Emma,

Have you tried a simpler model? False convergence can be due to an
overcomplex model. Can you give a brief outline of your data? E.g. how
many sites, how many data per site, ... Cross tabulations of all pairs
of factor variables are usefull too.

HTH,

Thierry 


------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

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

-----Oorspronkelijk bericht-----
Van: Emma Stone [mailto:Emma.Stone at bristol.ac.uk] 
Verzonden: vrijdag 13 maart 2009 10:50
Aan: ONKELINX, Thierry; Emma Stone; r-help at r-project.org
Onderwerp: RE: [R] Mixed models fixed effects

Hi Thierry,

That's great thanks!

I have done as you have said but I keep getting a warning message here
is 
my code:

G1Hvol<-glmer(passes~hvolume+style+habitat(1|Site),family = poisson)

And this is the message i get:
Warning message:
In mer_finalize(ans) : false convergence (8)

any ideas??

Emma


--On 11 March 2009 15:45 +0100 "ONKELINX, Thierry"

        
<Thierry.ONKELINX at inbo.be> wrote:

        

            

      
      
      
    

        
continuous

            

      
      
      
    

        
counts

            

      
      
      
    

        
poisson)

            

      
      
      
    

        
R-Sig-MixedModels

            

      
      
      
    

        
------------------------------------------------------------------------

            

      
      
      
    

        
more

            

      
      
      
    

        
to

            

      
      
      
    

        
not

            

      
      
      
    

        
[mailto:r-help-bounces at r-project.org]

            

      
      
      
    

        
model

            

      
      
      
    

        
So

            

      
      
      
    

        
is

            

      
      
      
    

        

      
      
    

        
schrijver

            

      
      
      
    

        
niet

            

      
      
      
    

        
in

            

      
      
      
    

        
be

            

      
      
      
    

        
message

            

      
      
      
    

        
----------------------
Emma Stone
Postgraduate Researcher
Bat Ecology and Bioacoustics Lab
& Mammal Research Unit
School of Biological Sciences,
University of Bristol, Woodland Road,
Bristol, BS8 1UG
Email: emma.stone at bristol.ac.uk



Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer 
en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document. The views expressed in  this message 
and any annex are purely those of the writer and may not be regarded as stating 
an official position of INBO, as long as the message is not confirmed by a duly 
signed document.

  
  


  


      

    

    

      
      

        


  

        

      Emma Stone
    

    

      
      #
    

  


  

      
Hi Thierry,

Thanks, my data are pasted in below: n = 48, with different numbers if site 
replicates.

   Site passes length width height ohwidth ohheight style shape nogap pgaps
1     1     32  38.21  7.18   2.60    0.00     0.00     1     1     0  0.00
2     1      7 154.38  2.55   2.43    0.00     0.00     2     1     0  0.00
3     2     24 130.00  2.73   4.96    5.83     2.27     1     2     0  1.92
4     2     43 130.00  2.73   4.96    3.45     2.45     1     2     0  1.91
5     2     32 130.00  3.30   4.34    3.67     2.63     3     2     0  0.00
6     2      9 130.00  3.30   4.34    2.13     1.53     2     2     0  0.00
7     2     25 214.00  1.65   6.23    2.80     2.53     3     2     0  0.00
8     2      1 214.00  2.20   1.05    0.00     0.00     2     1     0  0.00
9     2     57 188.00  5.87   4.97    3.23     2.13     2     2     0  0.00
10    2     32 211.00  2.63   6.09    4.37     2.50     2     2     0  0.00
11    2     14 211.00  2.63   6.09    3.50     2.53     2     2     0  0.00
12    3     78 192.00  2.30   2.40    0.33     0.88     2     2     0  2.19
13    3     11 192.00  2.50   2.50    0.13     0.55     2     2     0  2.19
14    3      9 444.00  2.10   1.93    0.00     0.00     2     1     2  6.19
15    4     40  44.00  1.83   2.05    0.00     0.00     1     1     1 31.81
16    4    112  44.00  1.58   1.73    0.00     0.00     1     1     1 31.81
17    4     23  98.00  2.18   1.70    0.00     0.00     1     3     0  2.55
18    4     23  98.00  1.78   1.60    0.00     0.00     1     1     0  2.55
19    4      4  84.00  1.73   1.98    0.00     0.00     1     3     1 17.02
20    4     72  88.00  3.30   5.30    3.30     1.45     1     2     0  0.00
21    5    207 116.00  3.08   3.38    3.65     3.68     1     2     0  0.00
22    5      2 116.00  2.85   2.18    3.18     3.53     1     2     0  0.00
23    5     81 104.00  2.68   2.78    1.00     0.75     2     1     0  0.00
24    5      3 104.00  2.68   2.38    0.00     0.00     2     1     0  0.00
25    5     21  59.00  2.78   4.03    2.23     1.75     2     2     0  6.78
26    5      1  59.00  2.78   3.33    1.38     1.35     2     2     0  6.78
27    6     82 165.56  2.50   4.00    1.00     1.33     1     2     0  0.00
28    6      1 165.56  2.60   3.63    0.50     1.40     1     2     0  0.00
29    6     46  69.35  3.23  10.67    4.73     4.67     1     2     0  0.00
30    6      7 165.56  3.50  10.17    2.67     1.67     1     2     0  0.00
31    6     45 136.00  3.33   3.67    0.00     0.00     1     2     0  2.20
32    6      3 136.00  3.33   2.75    0.00     0.00     1     2     0  3.30
33    6     34  82.00  2.83  12.00    3.33     3.83     1     2     0  0.00
34    7      0 228.00  2.57   2.70    0.30     1.00     2     2     0  0.50
35    7    148 228.00  3.08   4.68    0.75     1.75     2     2     0  0.05
36    7      0 208.00  2.40   2.90    0.00     0.00     2     1     0  1.44
37    7     38 208.00  2.57   2.63    0.00     0.00     2     1     0  1.44
38    7      0 112.00  2.13   1.65    0.00     0.00     2     1     0  0.50
39    7      0 192.00  1.55   1.55    0.00     0.00     2     1     0  0.00
40    7      0 132.00  1.56   1.41    0.00     0.00     2     1     0  0.00
41    8     52 148.00  5.05   7.62    2.55     3.38     2     2     0  0.00
42    8     18 148.00  4.08   5.80    0.65     0.63     2     2     0  0.00
43    8     19 210.00  3.08   4.58    0.70     0.88     2     2     0  1.42
44    8      0 210.00  3.68   4.90    0.25     0.38     3     2     0  1.42
45    8      3 246.00  2.18   2.43    0.00     0.00     2     1     3 15.24
46    8      0 246.00  1.93   2.20    0.00     0.00     2     1     3 15.24
47    8      3 142.00  1.60   2.03    0.00     0.00     1     1     3 26.19
48    8      0 142.00  1.37   1.87    0.00     0.00     1     1     3 26.19
   habitat side  oharea hvolume
1        1    2    0.00  713.30
2        1    4    0.00  956.62
3        1    2 1720.43 1760.30
4        1    4 1098.83 1760.30
5        1    4 1254.77 1861.86
6        1    2  423.66 1861.86
7        1    1 1515.98 2199.81
8        1    3    0.00  494.34
9        1    2 1293.42 5484.69
10       1    3 2305.18 3379.52
11       1    1 1868.41 3379.52
12       1    2   55.76 1059.84
13       1    4   13.73 1200.00
14       1    1    0.00 1799.53
15       1    1    0.00  165.07
16       1    3    0.00  120.27
17       1    2    0.00  363.19
18       1    4    0.00  279.10
19       1    4    0.00  287.73
20       1    2  421.08 1539.12
21       1    2 1558.11 1207.61
22       2    4 1302.15  720.71
23       2    2   78.00  774.84
24       1    4    0.00  663.35
25       1    2  230.25  661.00
26       1    4  109.92  546.19
27       1    3  220.19 1655.60
28       3    1  115.89 1562.56
29       1    1 1531.88 2390.09
30       1    3  738.22 5893.11
31       2    2    0.00 1662.07
32       4    4    0.00 1245.42
33       5    3 1045.82 2784.72
34       1    2   68.40 1582.09
35       1    4  299.25 3286.48
36       1    2    0.00 1447.68
37       1    4    0.00 1405.89
38       4    3    0.00  393.62
39       4    1    0.00  461.28
40       4    1    0.00  290.35
41       1    4 1275.61 5695.19
42       1    2   60.61 3502.27
43       1    1  129.36 2962.34
44       1    3   19.95 3786.72
45       1    1    0.00 1303.16
46       1    3    0.00 1044.52
47       1    2    0.00  461.22
48       1    4    0.00  363.79


--On 13 March 2009 11:01 +0100 "ONKELINX, Thierry"

        
<Thierry.ONKELINX at inbo.be> wrote:

        

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        
----------------------
Emma Stone
Postgraduate Researcher
Bat Ecology and Bioacoustics Lab
& Mammal Research Unit
School of Biological Sciences,
University of Bristol, Woodland Road,
Bristol, BS8 1UG
Email: emma.stone at bristol.ac.uk

  
  


  


      

    

    

      
      

        


  

        

      ONKELINX, Thierry
    

    

      
      #
    

  


  

      
Dear Emma,

First of all make shure that style and habitat are factors (assuming
that they are categorical).

glmer(passes~hvolume+style+habitat(1|Site),family = poisson)

Style has 3 levels, habitat 5 levels. So your model needs to estimate 1
parameter for hvolume, 2 for style, 4 for habitat and 1 for site. In
total 8 parameters. A rule of thumbs tells you that you need about 10
samples for each parameter. Hence you dataset (n = 48) is to small for
this kind of model.

Aditionally the variable habitat has some rare levels. Only one occures
of levels 3 and 5, and just a few more for levels 2 and 4. This kind of
data won't give you reliable estimates for habitat. So I would suggest
to drop this from your model.

HTH,

Thierry 


------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

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

-----Oorspronkelijk bericht-----
Van: Emma Stone [mailto:Emma.Stone at bristol.ac.uk] 
Verzonden: vrijdag 13 maart 2009 11:08
Aan: ONKELINX, Thierry; Emma Stone; r-help at r-project.org
Onderwerp: RE: [R] Mixed models fixed effects

Hi Thierry,

Thanks, my data are pasted in below: n = 48, with different numbers if
site 
replicates.

   Site passes length width height ohwidth ohheight style shape nogap
pgaps
1     1     32  38.21  7.18   2.60    0.00     0.00     1     1     0
0.00
2     1      7 154.38  2.55   2.43    0.00     0.00     2     1     0
0.00
3     2     24 130.00  2.73   4.96    5.83     2.27     1     2     0
1.92
4     2     43 130.00  2.73   4.96    3.45     2.45     1     2     0
1.91
5     2     32 130.00  3.30   4.34    3.67     2.63     3     2     0
0.00
6     2      9 130.00  3.30   4.34    2.13     1.53     2     2     0
0.00
7     2     25 214.00  1.65   6.23    2.80     2.53     3     2     0
0.00
8     2      1 214.00  2.20   1.05    0.00     0.00     2     1     0
0.00
9     2     57 188.00  5.87   4.97    3.23     2.13     2     2     0
0.00
10    2     32 211.00  2.63   6.09    4.37     2.50     2     2     0
0.00
11    2     14 211.00  2.63   6.09    3.50     2.53     2     2     0
0.00
12    3     78 192.00  2.30   2.40    0.33     0.88     2     2     0
2.19
13    3     11 192.00  2.50   2.50    0.13     0.55     2     2     0
2.19
14    3      9 444.00  2.10   1.93    0.00     0.00     2     1     2
6.19
15    4     40  44.00  1.83   2.05    0.00     0.00     1     1     1
31.81
16    4    112  44.00  1.58   1.73    0.00     0.00     1     1     1
31.81
17    4     23  98.00  2.18   1.70    0.00     0.00     1     3     0
2.55
18    4     23  98.00  1.78   1.60    0.00     0.00     1     1     0
2.55
19    4      4  84.00  1.73   1.98    0.00     0.00     1     3     1
17.02
20    4     72  88.00  3.30   5.30    3.30     1.45     1     2     0
0.00
21    5    207 116.00  3.08   3.38    3.65     3.68     1     2     0
0.00
22    5      2 116.00  2.85   2.18    3.18     3.53     1     2     0
0.00
23    5     81 104.00  2.68   2.78    1.00     0.75     2     1     0
0.00
24    5      3 104.00  2.68   2.38    0.00     0.00     2     1     0
0.00
25    5     21  59.00  2.78   4.03    2.23     1.75     2     2     0
6.78
26    5      1  59.00  2.78   3.33    1.38     1.35     2     2     0
6.78
27    6     82 165.56  2.50   4.00    1.00     1.33     1     2     0
0.00
28    6      1 165.56  2.60   3.63    0.50     1.40     1     2     0
0.00
29    6     46  69.35  3.23  10.67    4.73     4.67     1     2     0
0.00
30    6      7 165.56  3.50  10.17    2.67     1.67     1     2     0
0.00
31    6     45 136.00  3.33   3.67    0.00     0.00     1     2     0
2.20
32    6      3 136.00  3.33   2.75    0.00     0.00     1     2     0
3.30
33    6     34  82.00  2.83  12.00    3.33     3.83     1     2     0
0.00
34    7      0 228.00  2.57   2.70    0.30     1.00     2     2     0
0.50
35    7    148 228.00  3.08   4.68    0.75     1.75     2     2     0
0.05
36    7      0 208.00  2.40   2.90    0.00     0.00     2     1     0
1.44
37    7     38 208.00  2.57   2.63    0.00     0.00     2     1     0
1.44
38    7      0 112.00  2.13   1.65    0.00     0.00     2     1     0
0.50
39    7      0 192.00  1.55   1.55    0.00     0.00     2     1     0
0.00
40    7      0 132.00  1.56   1.41    0.00     0.00     2     1     0
0.00
41    8     52 148.00  5.05   7.62    2.55     3.38     2     2     0
0.00
42    8     18 148.00  4.08   5.80    0.65     0.63     2     2     0
0.00
43    8     19 210.00  3.08   4.58    0.70     0.88     2     2     0
1.42
44    8      0 210.00  3.68   4.90    0.25     0.38     3     2     0
1.42
45    8      3 246.00  2.18   2.43    0.00     0.00     2     1     3
15.24
46    8      0 246.00  1.93   2.20    0.00     0.00     2     1     3
15.24
47    8      3 142.00  1.60   2.03    0.00     0.00     1     1     3
26.19
48    8      0 142.00  1.37   1.87    0.00     0.00     1     1     3
26.19
   habitat side  oharea hvolume
1        1    2    0.00  713.30
2        1    4    0.00  956.62
3        1    2 1720.43 1760.30
4        1    4 1098.83 1760.30
5        1    4 1254.77 1861.86
6        1    2  423.66 1861.86
7        1    1 1515.98 2199.81
8        1    3    0.00  494.34
9        1    2 1293.42 5484.69
10       1    3 2305.18 3379.52
11       1    1 1868.41 3379.52
12       1    2   55.76 1059.84
13       1    4   13.73 1200.00
14       1    1    0.00 1799.53
15       1    1    0.00  165.07
16       1    3    0.00  120.27
17       1    2    0.00  363.19
18       1    4    0.00  279.10
19       1    4    0.00  287.73
20       1    2  421.08 1539.12
21       1    2 1558.11 1207.61
22       2    4 1302.15  720.71
23       2    2   78.00  774.84
24       1    4    0.00  663.35
25       1    2  230.25  661.00
26       1    4  109.92  546.19
27       1    3  220.19 1655.60
28       3    1  115.89 1562.56
29       1    1 1531.88 2390.09
30       1    3  738.22 5893.11
31       2    2    0.00 1662.07
32       4    4    0.00 1245.42
33       5    3 1045.82 2784.72
34       1    2   68.40 1582.09
35       1    4  299.25 3286.48
36       1    2    0.00 1447.68
37       1    4    0.00 1405.89
38       4    3    0.00  393.62
39       4    1    0.00  461.28
40       4    1    0.00  290.35
41       1    4 1275.61 5695.19
42       1    2   60.61 3502.27
43       1    1  129.36 2962.34
44       1    3   19.95 3786.72
45       1    1    0.00 1303.16
46       1    3    0.00 1044.52
47       1    2    0.00  461.22
48       1    4    0.00  363.79


--On 13 March 2009 11:01 +0100 "ONKELINX, Thierry"

        
<Thierry.ONKELINX at inbo.be> wrote:

        

            

      
      
      
    

        
------------------------------------------------------------------------

            

      
      
      
    

        
more

            

      
      
      
    

        
to

            

      
      
      
    

        
not

            

      
      
      
    

        
------------------------------------------------------------------------

            

      
      
      
    

        
Nature

            

      
      
      
    

        
covered

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        
expressed

            

      
      
      
    

        
not

            

      
      
      
    

        
schrijver

            

      
      
      
    

        
niet

            

      
      
      
    

        
in

            

      
      
      
    

        
be

            

      
      
      
    

        
message

            

      
      
      
    

        
----------------------
Emma Stone
Postgraduate Researcher
Bat Ecology and Bioacoustics Lab
& Mammal Research Unit
School of Biological Sciences,
University of Bristol, Woodland Road,
Bristol, BS8 1UG
Email: emma.stone at bristol.ac.uk



Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer 
en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document. The views expressed in  this message 
and any annex are purely those of the writer and may not be regarded as stating 
an official position of INBO, as long as the message is not confirmed by a duly 
signed document.

  
  


  


      

    

    

      
      

        


  

        

      Emma Stone
    

    

      
      #
    

  


  

      
Hi Thierry,

Thanks again! You are a great help!!

I have taken habitat out, and then run it with style but still the same 
problem exists, so I have taken both style and habitat out. The problem 
here is it leaves me with only 3 parameters and because they are all 
correlated I cant use them in the same models, so I just have 3 single 
models (one for each parameter) - which isnt ideal.

G3Pgaps<-glmer(passes~pgaps+(1|Site),family=poisson)
C1Hvol<-glmer(passes~hvolume+(1|Site))
C2OHArea<-glmer(passes~oharea+(1|Site))

Also, when I run the C1 and C2 model, it wont work if I state family 
poisson.

Is there anyway I can get rid of the correlations in the parameters so that 
I can use them in the same model? Or is there another option to boost n, ie 
bootsrapping??

Thanks again

Emma

--On 13 March 2009 11:21 +0100 "ONKELINX, Thierry"

        
<Thierry.ONKELINX at inbo.be> wrote:

        

            

      
      
      
    

        
----------------------
Emma Stone
Postgraduate Researcher
Bat Ecology and Bioacoustics Lab
& Mammal Research Unit
School of Biological Sciences,
University of Bristol, Woodland Road,
Bristol, BS8 1UG
Email: emma.stone at bristol.ac.uk