betabinomialcsi: Beta-Binomial probabilities of ordinal responses, given feeling parameter for each observation

Description

Compute the Beta-Binomial probabilities of given ordinal responses, with feeling parameter specified for each observation, and with the same overdispersion parameter for all the responses.

Usage

betabinomialcsi(m,ordinal,csivett,phi)

Value

A vector of the same length as ordinal: each entry is the Beta-Binomial probability for the given observation for the corresponding feeling and overdispersion parameters.

Arguments

m: Number of ordinal categories
ordinal: Vector of ordinal responses. Missing values are not allowed: they should be preliminarily deleted or imputed
csivett: Vector of feeling parameters of the Beta-Binomial distribution for given ordinal responses
phi: Overdispersion parameter of the Beta-Binomial distribution

References

Iannario, M. (2014). Modelling Uncertainty and Overdispersion in Ordinal Data, Communications in Statistics - Theory and Methods, 43, 771--786
Piccolo D. (2015). Inferential issues for CUBE models with covariates. Communications in Statistics - Theory and Methods, 44(23), 771--786.

Examples

Run this code

data(relgoods)
m<-10
ordinal<-relgoods$Tv
age<-2014-relgoods$BirthYear
no_na<-na.omit(cbind(ordinal,age))
ordinal<-no_na[,1]; age<-no_na[,2]
lage<-log(age)-mean(log(age))
gama<-c(-0.61,-0.31)
phi<-0.16 
csivett<-logis(lage,gama)
pr<-betabinomialcsi(m,ordinal,csivett,phi)
plot(density(pr))

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