glm: Fitting Generalized Linear Models

In safeBinaryRegression: Safe Binary Regression

Description

This function overloads the glm function so that a check for the existence of the maximum likelihood estimate is computed before fitting a ‘glm’ with a binary response.

Usage

glm(formula, family = gaussian, data, weights, subset, na.action, start = NULL,
	etastart, mustart, offset, control = glm.control(...), model = TRUE,
	method = "glm.fit", x = FALSE, y = TRUE, contrasts = NULL, ...,
	separation = c("find", "test"))

Arguments

The arguments are identical to the arguments of the glm function provided in the ‘stats’ package with the exception of

separation

either “find” or “test”. Both options prevent the model from being fit to binary data when the maximum likelihood estimate does not exist. Additionally, when separation = "find", the terms separating the sample points are identified when the maximum likelihood estimate is found not to exist.

The following arguments are passed to the glm function:

formula	see glm
family	see glm
data	see glm
weights	see glm
subset	see glm
na.action	see glm
start	see glm
etastart	see glm
mustart	see glm
offset	see glm
control	see glm
model	see glm
method	see glm
x	see glm
y	see glm
contrasts	see glm
...	see glm

Details

This function checks for the existence of the maximum likelihood estimate before the ‘glm’ function is used to fit binary regression models by solving the linear program proposed in Konis (2007).

Value

See the return value for the glm function.

Author(s)

Kjell Konis [e-mail]

References

Kjell Konis (2007). Linear programming algorithms for detecting separated data in binary logistic regression models. DPhil, University of Oxford http://ora.ouls.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a

See Also

glm.

Examples

## A set of 4 completely separated sample points ##
x <- c(-2, -1, 1, 2)
y <- c(0, 0, 1, 1)

## Not run: glm(y ~ x, family = binomial)


## A set of 4 quasicompletely separated sample points ##
x <- c(-2, 0, 0, 2)
y <- c(0, 0, 1, 1)

## Not run: glm(y ~ x, family = binomial)

Example output

Loading required package: lpSolveAPI

Attaching package: 'safeBinaryRegression'

The following object is masked from 'package:stats':

    glm

safeBinaryRegression documentation built on May 2, 2019, 4:45 p.m.