Re: [R] Mixed models fixed effects
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.onkel...@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.st...@bristol.ac.uk] Verzonden: vrijdag 13 maart 2009 10:50 Aan: ONKELINX, Thierry; Emma Stone; r-help@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.onkel...@inbo.be wrote: 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.onkel...@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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Emma Stone Verzonden: woensdag 11 maart 2009 15:29 Aan: r-help@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@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. -- 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.st...@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
Re: [R] Mixed models fixed effects
0.00 1447.68 37 140.00 1405.89 38 430.00 393.62 39 410.00 461.28 40 410.00 290.35 41 14 1275.61 5695.19 42 12 60.61 3502.27 43 11 129.36 2962.34 44 13 19.95 3786.72 45 110.00 1303.16 46 130.00 1044.52 47 120.00 461.22 48 140.00 363.79 --On 13 March 2009 11:01 +0100 ONKELINX, Thierry thierry.onkel...@inbo.be wrote: 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.onkel...@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.st...@bristol.ac.uk] Verzonden: vrijdag 13 maart 2009 10:50 Aan: ONKELINX, Thierry; Emma Stone; r-help@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.onkel...@inbo.be wrote: 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.onkel...@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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Emma Stone Verzonden: woensdag 11 maart 2009 15:29 Aan: r-help@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@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. -- Emma Stone Postgraduate Researcher Bat Ecology
Re: [R] Mixed models fixed effects
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.onkel...@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.st...@bristol.ac.uk] Verzonden: vrijdag 13 maart 2009 11:08 Aan: ONKELINX, Thierry; Emma Stone; r-help@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 2.600.00 0.00 1 1 0 0.00 2 1 7 154.38 2.55 2.430.00 0.00 2 1 0 0.00 3 2 24 130.00 2.73 4.965.83 2.27 1 2 0 1.92 4 2 43 130.00 2.73 4.963.45 2.45 1 2 0 1.91 5 2 32 130.00 3.30 4.343.67 2.63 3 2 0 0.00 6 2 9 130.00 3.30 4.342.13 1.53 2 2 0 0.00 7 2 25 214.00 1.65 6.232.80 2.53 3 2 0 0.00 8 2 1 214.00 2.20 1.050.00 0.00 2 1 0 0.00 9 2 57 188.00 5.87 4.973.23 2.13 2 2 0 0.00 102 32 211.00 2.63 6.094.37 2.50 2 2 0 0.00 112 14 211.00 2.63 6.093.50 2.53 2 2 0 0.00 123 78 192.00 2.30 2.400.33 0.88 2 2 0 2.19 133 11 192.00 2.50 2.500.13 0.55 2 2 0 2.19 143 9 444.00 2.10 1.930.00 0.00 2 1 2 6.19 154 40 44.00 1.83 2.050.00 0.00 1 1 1 31.81 164112 44.00 1.58 1.730.00 0.00 1 1 1 31.81 174 23 98.00 2.18 1.700.00 0.00 1 3 0 2.55 184 23 98.00 1.78 1.600.00 0.00 1 1 0 2.55 194 4 84.00 1.73 1.980.00 0.00 1 3 1 17.02 204 72 88.00 3.30 5.303.30 1.45 1 2 0 0.00 215207 116.00 3.08 3.383.65 3.68 1 2 0 0.00 225 2 116.00 2.85 2.183.18 3.53 1 2 0 0.00 235 81 104.00 2.68 2.781.00 0.75 2 1 0 0.00 245 3 104.00 2.68 2.380.00 0.00 2 1 0 0.00 255 21 59.00 2.78 4.032.23 1.75 2 2 0 6.78 265 1 59.00 2.78 3.331.38 1.35 2 2 0 6.78 276 82 165.56 2.50 4.001.00 1.33 1 2 0 0.00 286 1 165.56 2.60 3.630.50 1.40 1 2 0 0.00 296 46 69.35 3.23 10.674.73 4.67 1 2 0 0.00 306 7 165.56 3.50 10.172.67 1.67 1 2 0 0.00 316 45 136.00 3.33 3.670.00 0.00 1 2 0 2.20 326 3 136.00 3.33 2.750.00 0.00 1 2 0 3.30 336 34 82.00 2.83 12.003.33 3.83 1 2 0 0.00 347 0 228.00 2.57 2.700.30 1.00 2 2 0 0.50 357148 228.00 3.08 4.680.75 1.75 2 2 0 0.05 367 0 208.00 2.40 2.900.00 0.00 2 1 0 1.44 377 38 208.00 2.57 2.630.00 0.00 2 1 0 1.44 387 0 112.00 2.13 1.650.00 0.00 2 1 0 0.50 397 0 192.00 1.55 1.550.00 0.00 2 1 0 0.00 407 0 132.00 1.56 1.410.00 0.00 2 1 0 0.00 418 52 148.00 5.05 7.622.55
Re: [R] Mixed models fixed effects
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.onkel...@inbo.be wrote: poisson -- 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.st...@bristol.ac.uk __ R-help@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.
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@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.
Re: [R] Mixed models fixed effects
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.onkel...@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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Emma Stone Verzonden: woensdag 11 maart 2009 15:29 Aan: r-help@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@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. __ R-help@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.
Re: [R] Mixed models fixed effects
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. 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.onkel...@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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Emma Stone Verzonden: woensdag 11 maart 2009 15:29 Aan: r-help@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@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. __ R-help@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. __ R-help@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.
Re: [R] Mixed models fixed effects
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: 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. 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.onkel...@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-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Emma Stone Verzonden: woensdag 11 maart 2009 15:29 Aan: r-help@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@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. __ R-help@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. __ R-help@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. -- View this message in context: http://www.nabble.com/Re%3A-Mixed-models-fixed-effects-tp22456368p22460248.html Sent from the R help mailing list archive at Nabble.com. __ R-help@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.
