ordregr {ordgam}

Fit a proportional odds model for ordinal data

Description

Fit a proportional odds model for ordinal data

Usage

ordregr(
  y,
  nc = NULL,
  Xcal = Xcal,
  descending = FALSE,
  prior = list(mean = NULL, Prec = NULL),
  theta0 = NULL,
  ci.level = 0.95
)

Arguments

y

Vector containing the ordinal response (coded using integers in 1:nc).

nc

(optional) Maximum value of y.

Xcal

Design matrix (excluding intercept columns).

descending

Logical indicating if the odds of the response taking a value in the upper scale should be preferred over values in the lower scale.

prior

(optional) List giving the 'mean' and 'Prec'(ision) of the regression parameters.

theta0

(Optional) Vector containing starting values for the regression parameters.

ci.level

Confidence levels of the computed credible intervals for the regression parameters.

Value

An object of class ordregr.object.

Author(s)

Philippe Lambert [e-mail]

References

Lambert, P. and Gressani, 0. (2023) Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models. Statistical Modelling. <doi:10.1177/1471082X231181173>. Preprint: <arXiv:2210.01668>.

See Also

ordgam, ordregr.object.

Examples

library(ordgam)
data(freehmsData)
Xcal = with(freehmsData, cbind(gndr,eduyrs,age))
mod = ordregr(y=freehmsData$freehms, Xcal=Xcal, descending=TRUE)
print(mod)