betabinomialcsi function

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

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.

betabinomialcsi(m,ordinal,csivett,phi)

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

Returns

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.

Examples

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))

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.

See Also

betar, betabinomial