[R-sig-ME] Factor response and explanatory variables

Iker Vaquero Alba karraspito at yahoo.es
Thu Sep 17 16:16:45 CEST 2015

   Hello everyone,
  First of all, this is the same message I have sent to the general list before, I think it's more appropriate here.
   I am going to ask this certainly tricky question here not (yet) with the intention of getting a definitive answer, as I need to deepen my questions much more, but just to have an approximate idea of which direction taking next. 
   I have a dataset where the potential response variables are categorical multinomial (ordered, I think): several people were asked to give a value from 1 to 5 to several attributes in a potential partner, both for a short term commitment or for a longer relationship. The age, religion, sexual orientation, sexual identity (gender), self-perceived sexual attractivess and minimum attractiveness demanded in a potential partner (this ones also with values 1 to 5) were recorded for each participant.   The idea is using the values given to attributes in potential partners as the response variable, and see to what extent these are influenced by the person's age, gender, religion and so on. 
   The problem is that all my variables are factors, I have no numeric ones. Also, as the values given to the same attributes for a short term commitment of for a longer relationship are expected to be correlated, I was considering using multiple response variables, which adds even more difficulty to the model.
   I have been reading about MCMCglmm, the course notes, which are not easy to understand. In any case, at some point I have read that if I don't want to fit random effects (as I think it's my case), I'd better use the pscl package instead.

   Can you give me any advice at this point? Should I try and use pscl, or is it better to try with MCMCglmm given the difficulty of the model? Any little help will be highly appreciated. 

   Thank you very much

   Dr. Iker Vaquero-Alba
   Visiting Postdoctoral Research Associate
   Laboratory of Evolutionary Ecology of Adaptations 
   School of Life Sciences
   Joseph Banks Laboratories
   University of Lincoln   Brayford Campus, Lincoln
   LN6 7DL
   United Kingdom


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