ordglm: Generalized Linear Ordinal Regression Models

In gnlm: Generalized Nonlinear Regression Models

Description

ordglm fits linear regression functions with logistic or probit link to ordinal response data by proportional odds.

Usage

ordglm(formula, data = parent.frame(), link = "logit", maxiter = 10,
  weights = 1)

Arguments

formula	A model formula. The response must be integers numbered from zero to one less than the number of ordered categories.
data	An optional data frame containing the variables in the model.
link	Logit or probit link function.
maxiter	Maximum number of iterations allowed.
weights	A vector containing the frequencies for grouped data.

Value

A list of class ordglm is returned. The printed output includes the -log likelihood, the corresponding AIC, the deviance, the maximum likelihood estimates, standard errors, and correlations.

Author(s)

J.K. Lindsey, adapted and heavily modified from Matlab code (ordinalMLE) by J.H. Albert.

References

Jansen, J. (1991) Fitting regression models to ordinal data. Biometrical Journal 33, 807-815.

Johnson, V.E. and Albert, J.H. (1999) Ordinal Data Modeling. Springer-Verlag.

See Also

glm, nordr

Examples

# McCullagh (1980) JRSS B42, 109-142
# tonsil size: 2x3 contingency table
y <- c(0:2,0:2)
carrier <- gl(2,3,6)
wt <- c(19,29,24,497,560,269)
ordglm(y~carrier, weights=wt)

gnlm documentation built on May 2, 2019, 7:26 a.m.