Hello
After struggling with Crawley's and Pinheiro & Bates' books + scanning
the archiove for a day I feel compelled to ask thourgh this list.
There were two treatments of food; "Treatment" = "1" and "2". In each
treatment there were 60 females that ate the food and then laid one
clutch of eggs each. From each clutch I took 50 larvae and divided them
on 5 cups (with 10 larvae per cup). Then I let the larvae starve to
death and noted the day-of-death ("Deathday") for each larva.
The data set looks like this:
Treatment Clutch Cup Larva DeathDay
1 2 1 1 2
1 2 1 2 2
1 2 1 3 2
1 2 1 4 2
1 2 1 5 4
1 2 1 6 4
1 2 1 7 4
1 2 1 8 4
1 2 1 9 6
1 2 1 10 6
1 2 2 1 2
1 2 2 2 4
1 2 2 3 9... and so on
What I'm interested in is the effect of the fixed factor "Treatment" on
"DeathDay". The unit of replication is "Clutch".
However, I want to use a model where the variation within Clutch and
within Cup is taken into account, while avoiiding pseudoreplication of 5
cups (and 50 larvae) coming from the same clutch.
I guess the solution is a mixed model, with "Cup" nested in "Clutch"
nested in "Treatment" and with "Cup" and "Clutch" as random factors, while
"Treatment" is a fixed factor.
I now have trouble writing the syntax. I was recommended this by one expert:
model1<-lme(DeathDay~Treatment,random=~Treatment|Clutch/Cup)
But after consulting various books, I wonder if it is right. Treatment
is fixed factor, so what is it doing left od the |?. I think I should
write it like this:
model2<-lme(DeathDay~ Treatment,random=~1|Clutch/Cup)
And then, to test if Treatment had an effect do a model comparison
model3<-lme(DeathDay~ 1,random=~1|Clutch/Cup)
anova(model2,model3)
Which of model1 and 2 is right? Perhaps neither? If not, I would be
thankful for any suggestions on a proper model.
Sincerely
Andreas Svensson
PS I have the corresponding script for SPSS, which might clarify my
question for you:
glm
DeathDay by Cup Clutch Treatment
/method=sstype(1)
/random Cup Clutch
/design Treatment Clutch(Treatment) Cup(Clutch(Treatment)).
|