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
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.
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.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. > > ______________________________________________ > 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. >
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.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. >> >> ______________________________________________ >> 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. >> > > ______________________________________________ > 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. > >-- 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.