[R] Constructing a model with multilevel response variables
Sam
Sam_Smith at me.com
Tue Jun 29 14:11:28 CEST 2010
Dear List,
I am a little unsure how to structure my model and was after some advice. I am a little unsure if this question is appropriate for this list, if it is not please just delete and accept my apologise.
I have 10 factors that are categorical variables and 5 levels of response variables -
A B C D - Factors RESPONSE
2 2 2 2 1
2 4 2 2 2
2 1 2 2 2
2 1 2 1 1
2 3 2 2 3
2 1 1 2 4
2 1 2 3 4
1 1 3 2 2
2 2 2 2 1
2 1 5 2 1
The response variables relate to how threatened the species is - from not threatened to extinct (1-5)
My first approach was to divide the 5 response levels into 2 - threatened ( levels 1+2) or non threatened (levels 3,4+5) and call
model1 <- lmer(THREAT~1+(1|ORDER/FAMILY) + A+B+C+D...., family=binomial)
Which worked well, now i want to see how the factors influence the individual response variables i.e do species with a response variable of 1for instance, posses certain factors, and it is this i am unsure how to build into a model.
My overall goal would be to use the model as a predictive model and ask - "if a species has factors a ,b,c for instance , can i predict what the response level (0-5) would be"
Thanks, and once again i apologise if this is not the right place to ask this type of question.
Sam,
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