[R] binomia data and mixed model

[Lorenz.Gygax@fat.admin.ch]

> The experimental design was suppose to consist of 4 
> treatments replicated 3 time, Source 1 and applied at 10 cm 
> and source 2 applied at 20 cm. During the construction of the
> treatmetns the depths vary considerably so i can't test all my
> samples based on 10 and 20 cm any more the depths are now
> considered random and not fixed.

It is not really clear what you measuring ... but do you know the depth even
if it is not exactly 10 and 20 cm? Then, perhaps you could use this variable
in a continous fashion but still as fixed? I do not really see how you can
treat such a variable as random.

> The data is very non-normal (lots of zeros) therefore the only way 
> to analyze it is to convert to binomial data.

I doubt this is the only way but certainly a valid one.

> Does any one know what type of analysis I should use? I was told
> that a NLmixed model would work but also a GLIM mixed model was
> appropriate. Is there any info using these in R.

I do not know about those but you can conduct binomial mixed effects models
by either using glmmPQL in library 'MASS' or GLMM in library 'lme4'.

Also do read:
  author = 	 {Pinheiro, Jose C and Bates, Douglas M},
  title = 	 {Mixed-Effects Models in {S} and {S}-{P}{L}{U}{S}},
  publisher = 	 {Springer},
  year = 	 {2000},
  address = 	 {New York}
and
	AUTHOR = {Venables, W N and Ripley, B D},
	TITLE = {Modern Applied Statistics with {S}},
	PUBLISHER = {Springer},
	YEAR = {2002},
	ADDRESS = {New York},
	EDITION = {fourth}

Regards, Lorenz
- 
Lorenz Gygax, Dr. sc. nat.
Centre for proper housing of ruminants and pigs
Swiss Federal Veterinary Office
agroscope FAT Tänikon, CH-8356 Ettenhausen / Switzerland