Hello to everyone, after much reading I decided to write because I cannot find a solution to my question. I already did a priori contrasts before for a continuous variable with normal distribution. Now I have another variable (burrow), which is binomial, and I can do the GLM for it. But when I do the a priori contrasts, it has no result in the cases where all data are 0 (is not that there are no data, they are just all 0 in a category (treat 30-30), and I want to compare this with others that have ones). Data sructure is like this:>head(burrow)date day treat psu sp burrow 1 3 0 30-30 36 B 0 2 3 0 30-30 36 B 0 3 3 0 15-30 36 B 1 4 3 0 15-30 36 B 1 5 3 0 15-30 36 B 1 6 3 0 10-25 36 B 1 My model is this:>model4B2<-glm(burrow~ treat, family=binomial(link="logit"), data=D4B)And I did the contrast like this:>require(multcomp)#Test contrastes 30 vs all (there are 4 categories to compare) k3010R1<-matrix(c(3,-1,-1,-1),1) k3010R1 t3010<-glht(model4B3.2,linfct=k3010R1) summary(t3010) But is not working and I am sure it should work. Could it be because my explanatory variable is cathegorical? Or is just not possible to do contrasts for binomial when you have all 0 in some cathegory? Thank you in advance, -- Rula Dom?nguez Fern?ndez PhD Student *Departamento de Ecolox?a e Biolox?a Animal* *Faculdade de Ciencias do Mar* *Universidade de Vigo* www.researchgate.net/profile/Rula_Dominguez <https://www.researchgate.net/profile/Rula_Dominguez3> EcoCost <https://ecocost.webs.uvigo.es/index.php?option=com_content&view=article&id=9&Itemid=164&lang=gl> M?vil: +34 646521205 [[alternative HTML version deleted]]
Dear Rula That is really a statistical question not one for this list but the answer is that the fact that they are all zero for that category explains it. Search on-line for separation for more details. Michael On 18/01/2019 09:56, Rula Dom?nguez wrote:> Hello to everyone, > > after much reading I decided to write because I cannot find a solution to > my question. > > I already did a priori contrasts before for a continuous variable with > normal distribution. Now I have another variable (burrow), which is > binomial, and I can do the GLM for it. But when I do the a priori > contrasts, it has no result in the cases where all data are 0 (is not that > there are no data, they are just all 0 in a category (treat 30-30), and I > want to compare this with others that have ones). > Data sructure is like this: > >> head(burrow) > date day treat psu sp burrow > 1 3 0 30-30 36 B 0 > 2 3 0 30-30 36 B 0 > 3 3 0 15-30 36 B 1 > 4 3 0 15-30 36 B 1 > 5 3 0 15-30 36 B 1 > 6 3 0 10-25 36 B 1 > > My model is this: >> model4B2<-glm(burrow~ treat, family=binomial(link="logit"), data=D4B) > > And I did the contrast like this: > >> require(multcomp) > #Test contrastes 30 vs all (there are 4 categories to compare) > k3010R1<-matrix(c(3,-1,-1,-1),1) > k3010R1 > t3010<-glht(model4B3.2,linfct=k3010R1) > summary(t3010) > > But is not working and I am sure it should work. > > Could it be because my explanatory variable is cathegorical? > Or is just not possible to do contrasts for binomial when you have all 0 in > some cathegory? > > Thank you in advance, >-- Michael http://www.dewey.myzen.co.uk/home.html