# Calculating goodness-of-fit measures

### Description

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

### Usage

1 2 3 4 |

### Arguments

`output` |
An object containing the output from the function |

`x` |
An object of class "gofm." |

`digits` |
A number of significant digits. |

`...` |
Arguments passed to the function |

### 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.

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 |

`AdjRHO2` |
The rho-squared value adjusted by the number of estimated coefficients. Defined as |

`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

### References

Ben-Akiva, M. and Lerman, S. R. (1985) *Discrete Choice Analysis: Theory and Application to Travel Demand*. The MIT Press.

Cameron, A. C. and Trivedi, P. K. (2005) *Microeconometrics: Methods and Applications*. Cambridge University Press.

Aizaki, H. (2012) Basic Functions for Supporting an Implementation of Choice Experiments in R. *Journal of Statistical Software, Code Snippets*, **50**(2), 1–24. http://www.jstatsoft.org/v50/c02/

### See Also

`clogit`

, `glm`

, `make.dataset`

### Examples

1 | ```
# See "Examples" for the function make.dataset.
``` |