Re: [R] cross random effects (more information abuot the data)

[Spencer Graves]

     Have you read the posting guide 
(http://www.R-project.org/posting-guide.html)?  Also, can you produce a 
simpler example with a few lines of R code that someone could copy from 
your email and paste into R to illustrate your problem.  I don't have 
time to read your email, but if you could reduce it by a factor of about 
20, with a toy example that someone else could easily understand, you 
might more likely get the answer you are seeking.  (You might also find 
the answer to your question by following carefully the steps outlined in 
the posting guide and trying to produce a toy example as just suggested.) 

     I'm sorry I can't be of more help.  I know how frustrating it can 
be to struggle for days with a problem like this. 
     spencer graves

[EMAIL PROTECTED] wrote:
Dear friends,
I have asked last few days about cross-random effects
using PQL, but I have not receive any answer because
might my question was not clear.
My question was about analysing the salamander mating
data using PQL. This data contain cross-random effects
for (male) and for (female). By opining MASS and lme
library. I wrote this code
sala.glmm <- glmmPQL(fixed=y~WSf*WSM,
random=list(experiment=pdBlocked(list(pdIdent(~randf-1),pdIdent(~randm-1)))),
family=binomial, data=sala.data).
Where
data neame=sala.glmm which contain
y is response
wsf is fixed effect
wsm is fixed effects
randf  is random effect
random is random effect
The data contain three experiments at the same time.
The previous cod is work but it does not give me
accurate result especially for the random effects.
For experiment I wrote this code 

experiment <-
factor(c(rep(1,120),rep(2,120),rep(3,120)))
because I have three experiments at the same time,
but if I change the experiment to e.g
experiment <- factor(c(rep(1,360)))
is still give answer but is not the right answer. So,
I am accusing my specification of the experiment
(group). If you have any suggestion pleas let me know.
  E-mail:[EMAIL PROTECTED]
Here I am going to gve mre details about the data.
the
 

details about the data is:
   

The data are:
 

McCullagh and Nelder (1989,sec.14.5)polished an
interesting set of data on the success of matting
between male and female salamanders drawn from two
populations, the rough butts (RB) and the white
   

sides
 

(WS), that had been geographically isolated from
   

each
 

other. In the first of three experiments, conducted
during the summer of 1986, 10 RB females and 10 WS
females were mated with three RB males and three WS
males, for a total of six mating each over 24 days.
Each of 10 RB males and 10 WS males likewise served
   

as
 

mates for three females of each type. These same 40
salamanders were used in a repeat experiment
   

conducted
 

in the fall that involved no repetitions of the
earlier mal-female pairs. A third experiment, also
conducted in the fall, used a new set of 40 animals.
Each experiment involved 30 mating of each of the
   

four
 

gender-population combinations. Simple inspection of
the data revealed that three of the crosses had
success rates of about 70%, whereas the mating of WS
females with RB MALES WAS SUCCESSFUL ONLY 25% OF the
time. Evaluating the statistical significance of
   

these
 

differences was complicated by the fact that the 360
binary responses were not independent.
The model is used here is the mating probabilities
are assumed to be the same for each of the three
experiments. The random effects are assumed to be
independent in each experiment. The male and
Female effects are assumed to have different
   

variances
 

but the variances are assumed
To be the same across the three experiments.
     Best Regared
   

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