[R-sig-ME] Multi level response variables
cm744 at st-andrews.ac.uk
Tue Jun 29 13:57:28 CEST 2010
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 -
WOODYNONWOODY L2_REGIONS SEASONALITY FLORALSYMMETRY - Factors IUCN - RESPONSE
2 2 2 2 NE
2 4 2 2 LC
2 1 2 2 CR
2 1 2 1 NE
2 3 2 2 NE
2 1 1 2 NE
2 1 2 3 NT
1 1 3 2 NE
2 2 2 2 LC
2 1 5 2 LC
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) + STORAGE_ORGAN + BREEDING_SYSTEM + POLLEN_DISPERSAL + LIFE_FORM + FRUIT + ENDOSPERM + HABIT + WOODY_NONWOODY + L2_REGIONS + SEASONALITY + ALTITUDE + SEED_FRUIT + FLORAL_SYMMETRY, family=binomial)
Which worked well, now i want to see how the factors influence the individual response variables i.e do species with LC for instance, posses certain factors, and it is this i am unsure how to build into a lmer 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.
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