Hi
 I am a new user the R and I am very grateful for all your help but.......

I have a problem and I can't resolve yet. I am trying to get the contrasts for 
a binomial 3-way GLM (T= 4 temperature, t= 2 time and c= 2 substrate levels, 
plus treatment control) in total they are 17 treatments.

  

I have tried with the glht but this function only work for 1-way GLM, 

 

acacia<-cbind(g,N-g)

> acacia1<-glm(acacia~tratamiento,binomial)

 

> acacia2<-glht(acacia1, linfct = mcp(tratamiento = "Tukey"))

> summary(acacia2)

 

         Simultaneous Tests for General Linear Hypotheses

 

Multiple Comparisons of Means: Tukey Contrasts

 

 

Fit: glm(formula = acacia ~ tratamiento, family = binomial)

 

Linear Hypotheses:

            Estimate Std. Error z value p value    

B - A == 0    2.9073     1.0395   2.797  0.2417    

C - A == 0    4.0860     1.0227   3.995   <0.01 ** 

D - A == 0    4.8458     1.0207   4.748   <0.01 ***

E - A == 0    3.0445     1.0362   2.938  0.1727    

F - A == 0    3.3399     1.0306   3.241  0.0744 .........etc. 

 

If the GLM is with interactions don't work

 

Ø       acacia3<-glm(acacia~T*t*c,binomial)

Ø       > glht(acacia3, linfct = mcp(T = "Tukey"))

Ø       Error in modelparm.default(model, ...) : 

Ø         dimensions of coefficients and covariance matrix don't match

Ø       Warning message:

Ø       In mcp2matrix(model, linfct = linfct) :

Ø         covariate interactions found -- default contrast might be 
inappropriate

 

 

Other function could be simtes but this was deprecated from package multcomp

 

There are others options to get comparisons contrasts for model GLM with 
interactions? or this test don't exist ?

 

I hope help me 

 


        [[alternative HTML version deleted]]

______________________________________________
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.

Reply via email to