R: An object for modeling linear odds.

as.linodds {ohenery}

R Documentation

An object for modeling linear odds.

Description

A model for odds linear in some feature.

Usage

as.linodds(object, formula, beta)

## S3 method for class 'linodds'
predict(object, newdata, type = c("eta", "mu",
  "erank"), na.action = na.pass, group = NULL, ...)

## S3 method for class 'linodds'
coef(object, ...)

Arguments

`object`	some list-like object.
`formula`	an object of class `"formula"` (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under ‘Details’.
`beta`	the fit coefficients.
`newdata`	a `data.frame` from which we can extract a model frame via the formula of the `object`.
`type`	indicates which prediction should be returned: `eta` The odds. `mu` The probability. `erank` The expected rank.
`na.action`	How to deal with missing values in `y`, `g`, `X`, `wt`, `eta0`.
`group`	the string name of the group variable in the data, or a bare character with the group name. The group indices need not be integers, but that is more efficient. They need not be sorted.
`...`	other arguments.

Details

An object which holds a formula, some fit coefficients \beta which fit in that formula to generate odds in odds space. The odds can then be converted, via predict.linodds to probabilities, or to expected ranks under the Harville model. Both harsm and hensm return objects of class linodds.

We think of linear odds as \eta = x^{\top}\beta, for independent variables x. The odds, \eta are converted to probabilities, \mu via \mu = c \exp{\eta}, where the constant c is chosen so the \mu for a given matching sum to one.

Author(s)