chi2cub {CUB}R Documentation

Pearson X^2 statistic

Description

Compute the X^2 statistic of Pearson for CUB models with one or two discrete covariates for the feeling component.

Usage

chi2cub(m,ordinal,W,pai,gama)

Arguments

m

Number of ordinal categories

ordinal

Vector of ordinal responses

W

Matrix of covariates for the feeling component

pai

Uncertainty parameter

gama

Vector of parameters for the feeling component, with length equal to NCOL(W)+1 to account for an intercept term (first entry of gama)

Details

No missing value should be present neither for ordinal nor for covariate matrices: thus, deletion or imputation procedures should be preliminarily run.

Value

A list with the following components:

df

Degrees of freedom

chi2

Value of the Pearson fitting measure

dev

Deviance indicator

References

Tutz, G. (2012). Regression for Categorical Data, Cambridge University Press, Cambridge

Examples

data(univer)
m<-7
pai<-0.3
gama<-c(0.1,0.7)
ordinal<-univer$informat; W<-univer$gender;
pearson<-chi2cub(m,ordinal,W,pai,gama)
degfree<-pearson$df
statvalue<-pearson$chi2
deviance<-pearson$dev

[Package CUB version 1.1.4 Index]