Ordinal categorical variable as a random effect in MCMCglmm
Dear Jarrod, Thanks for your response. Quality is a ranking in the completeness/missingness of the data; a higher quality data point is scored higher. This is an attempt to control for potential missing information from the response variable. The response is a count (hence the family being Poisson), and the idea is that for each taxon on a phylogeny, there is a count variable, but that count could potentially be under-estimated based on the Quality of the data associated with each taxon. But in reality, this potential under-estimation is unknown and unmeasurable so Quality is just one attempt to control for this somewhat-known uncertainty. many thanks, Manabu
On 3 November 2014 14:22, Jarrod Hadfield <j.hadfield at ed.ac.uk> wrote:
Dear Manabu, Could you explain what Quality is? If it is ordered it is hard to see why you would be fitting it as random effect? Is this really your response variable? Cheers, Jarrod Quoting Manabu Sakamoto <manabu.sakamoto at gmail.com> on Wed, 29 Oct 2014 11:16:48 +0000: Dear list,
I'm using MCMCglmm with some random effects, including a phylogeny and a
categorical variable, scored along an ordinal scale, e.g., 1 < 2 < 3 <...
If my phylogenetic tip names are stored as a character string Taxon (and
there is an associated inverse A object), and my quality codes are stored
as an ordered factor variable Quality, then my questions are:
1) Can I specify the random effect formula simply as: random= ~ Taxon +
Quality --- i.e., without functions like us() or idh() around Quality?
2) What sort of prior should I assign for Quality? --- For the moment I am
using:
list(V=1, nu=1, alpha.mu = 0, alpha.V = 25^2)
I'd appreciate any advise.
Kind regards.
Manabu
--
Manabu Sakamoto, PhD
manabu.sakamoto at gmail.com
[[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
-- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.
Manabu Sakamoto, PhD manabu.sakamoto at gmail.com [[alternative HTML version deleted]]