Dear R users I have built the following model m1<-lmer(y~harn+foodn+(1|ass%in%pop%in%fam),family = "quasibinomial") where y<-cbind(alive,dead) where harn and foodn are categorical factors and the random effect is a nested term to represent experimental structure e.g. Day/Block/Replicate ass= 5 level factor, pop= 2 populations per treatment factor in each assay, 7 reps per population The model can be family = quasibinomial or binomial My complete lack of understanding is in retrieving the coefficients for the fixed effects to back-transform the effects of my factors on proportional survival I get the following output:> coef(m1)$`ass %in% pop %in% fam` (Intercept) harn1 harn2 foodn2 FALSE 1.0322375 -0.1939521 0.0310434 0.810084 TRUE 0.5997679 -0.1939521 0.0310434 0.810084 Where FALSE and TRUE refer to some attribute of the random effect My hunch is that it refers to the Coefficients with (=TRUE) and without (=FALSE) the random effects? Any help appreciated ........................................................................ ............ Dr Tom C Cameron Genetics, Ecology and Evolution IICB, University of Leeds Leeds, UK Office: +44 (0)113 343 2837 Lab: +44 (0)113 343 2854 Fax: +44 (0)113 343 2835 Email: t.c.cameron@leeds.ac.uk Webpage: click here <http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC> [[alternative HTML version deleted]]
The extractor function for the fixed effects is fixef(), not coef(). Out of curiosity, why are you using (1|ass%in%pop%in%fam)? This notation is non-standard and does not define the nesting structure of the data. I think you want (1|ass/pop/fam)> -----Original Message----- > From: r-help-bounces at r-project.org > [mailto:r-help-bounces at r-project.org] On Behalf Of Tom Cameron > Sent: Friday, August 08, 2008 11:47 AM > To: r-help at r-project.org; r-sig-mixed-models at r-project.org > Subject: [R] [lme4]Coef output with binomial lmer > > Dear R users > > I have built the following model > > m1<-lmer(y~harn+foodn+(1|ass%in%pop%in%fam),family = "quasibinomial") > > where y<-cbind(alive,dead) > > where harn and foodn are categorical factors and the random > effect is a nested term to represent experimental structure > e.g. Day/Block/Replicate ass= 5 level factor, pop= 2 > populations per treatment factor in each assay, 7 reps per population > > The model can be family = quasibinomial or binomial > > My complete lack of understanding is in retrieving the > coefficients for the fixed effects to back-transform the > effects of my factors on proportional survival > > I get the following output: > > coef(m1) > $`ass %in% pop %in% fam` > (Intercept) harn1 harn2 foodn2 > FALSE 1.0322375 -0.1939521 0.0310434 0.810084 > TRUE 0.5997679 -0.1939521 0.0310434 0.810084 > > Where FALSE and TRUE refer to some attribute of the random effect > > My hunch is that it refers to the Coefficients with (=TRUE) > and without > (=FALSE) the random effects? > > Any help appreciated > > > .............................................................. > .......... > ............ > Dr Tom C Cameron > Genetics, Ecology and Evolution > IICB, University of Leeds > Leeds, UK > Office: +44 (0)113 343 2837 > Lab: +44 (0)113 343 2854 > Fax: +44 (0)113 343 2835 > > > Email: t.c.cameron at leeds.ac.uk > Webpage: click here > <http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC> > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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 Tom,>> 1|ass%in%pop%in%famThis is "non-standard," but as you have found, it works. The correct translation is in fact 1|fam/pop/ass and not 1|ass/pop/fam as suggested by Harold Doran. Dropping %, ass%in%pop%in%fam reads [means] as: nest ass in pop [= pop/ass], and then nest this in fam == fam/pop/ass HTH, Mark. T.C. Cameron wrote:> > Dear R users > > I have built the following model > > m1<-lmer(y~harn+foodn+(1|ass%in%pop%in%fam),family = "quasibinomial") > > where y<-cbind(alive,dead) > > where harn and foodn are categorical factors and the random effect is a > nested term to represent experimental structure > e.g. Day/Block/Replicate > ass= 5 level factor, pop= 2 populations per treatment factor in each > assay, 7 reps per population > > The model can be family = quasibinomial or binomial > > My complete lack of understanding is in retrieving the coefficients for > the fixed effects to back-transform the effects of my factors on > proportional survival > > I get the following output: >> coef(m1) > $`ass %in% pop %in% fam` > (Intercept) harn1 harn2 foodn2 > FALSE 1.0322375 -0.1939521 0.0310434 0.810084 > TRUE 0.5997679 -0.1939521 0.0310434 0.810084 > > Where FALSE and TRUE refer to some attribute of the random effect > > My hunch is that it refers to the Coefficients with (=TRUE) and without > (=FALSE) the random effects? > > Any help appreciated > > > ........................................................................ > ............ > Dr Tom C Cameron > Genetics, Ecology and Evolution > IICB, University of Leeds > Leeds, UK > Office: +44 (0)113 343 2837 > Lab: +44 (0)113 343 2854 > Fax: +44 (0)113 343 2835 > > > Email: t.c.cameron at leeds.ac.uk > Webpage: click here > <http://www.fbs.leeds.ac.uk/staff/profile.php?tag=Cameron_TC> > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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/-lme4-Coef-output-with-binomial-lmer-tp18894407p18904468.html Sent from the R help mailing list archive at Nabble.com.