brant.test: Brant Test of the Proportional Odds Assumption

In ejikeugba/gofcat: Goodness-of-Fit Measures for Categorical Response Models

Brant Test of the Proportional Odds Assumption

Description

Provides the means of testing the parallel regression assumption in the ordinal regression models. Also available is the likelihood ratio test, LR.test().

Usage

brant.test(model, global= FALSE, call = FALSE)

Arguments

model	a single model object to be tested.
global	default to FALSE. When TRUE, a global test is made for the factor variables instead of the individual factor levels.
call	when TRUE the model call is printed alongside test results.

Details

The parallel regression assumption for the ordinal regression model can be tested With this function. The brant test (Brant, 1990) is currently available for objects of class: serp(), clm(), polr() and vglm(). Objects of class serp() should have the slope argument set to 'parallel', while objects of class vglm() should have the model argument TRUE, if not, the model is automatically updated to include the object 'model'. Moreover, family in vglm() must be either "cumulative" or "propodds", with the parallel argument TRUE.

Value

model	call of the model tested
df	the degrees of freedom
global	logical vector of TRUE or FALSE
modeltype	character vector of the class of model tested
Terms	original model terms
vnames	character vector of variable names used in the model
chisq	realized values of the chi-square statistic
rdf	residual degrees of freedom
rDev	residual deviance
prob	the p-values of test
call	a logical vector

References

Brant, R. (1990). Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics, 46, 1171-1178.

See Also

LR.test, hosmerlem, lipsitz, pulkroben

Examples

require(serp)

set.seed(1)
n <- 200
y <- ordered(rbinom(n, 2, 0.5))
x1 <- factor(rbinom(n, 2, 0.7))
x2 <- runif(n)

## proportional odds model
sp <- serp(y ~ x1 * x2, link = "logit", slope = "parallel", reverse = TRUE)

brant.test(sp)
brant.test(sp, global = TRUE, call=TRUE)

ejikeugba/gofcat documentation built on Feb. 3, 2023, 6:29 a.m.