[R] Constructing a model with multilevel response variables

From: Sam <Sam_Smith_at_me.com>
Date: Tue, 29 Jun 2010 05:11:28 -0700 (PDT)


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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