gofm: Calculating goodness-of-fit measures

In support.CEs: Basic Functions for Supporting an Implementation of Choice Experiments

Calculating goodness-of-fit measures

Description

This function provides rho-squared and rho-squared adjusted by the number of estimated coefficients.

Usage

gofm(output)

## S3 method for class 'gofm'
print(x, digits = getOption("digits"), ...)

Arguments

output	An object containing the output from the function clogit or glm.
x	An object of class "gofm."
digits	A number of significant digits.
...	Arguments passed to the function format.

Details

This function provides rho-squared (also called McFadden's R-squared or pseudo R-squared), rho-squared adjusted by the number of estimated coefficients, the number of estimated coefficients, and log likelihood values at the start and at convergence (see, e.g., Ben-Akiva and Lerman 1985; Cameron and Trivedi 2005).

In version 0.3-0 and later versions, this function is also available for calculating goodness-of-fit measures for binary choice models estimated by using the function glm in the package stats.

Value

This function returns an object of S3 class "gofm" that is a list with the following components.

RHO2	The rho-squared value. Defined as RHO2 = 1 - (LLb / LL0).
AdjRHO2	The rho-squared value adjusted by the number of estimated coefficients. Defined as AdjRHO2 = 1 - ((LLb - K) / LL0).
AIC	The Akaike Information Criterion (AIC).
BIC	The Bayesian Information Criterion.
K	The number of estimated coefficients.
LL0	The log likelihood value at the start.
LLb	The log likelihood value at convergence.

Author(s)

Hideo Aizaki

See Also

clogit, glm, make.dataset

Examples

# See "Examples" for the function make.dataset.

support.CEs documentation built on Nov. 3, 2023, 9:07 a.m.