Model evaluation methods based on the analogue of squared residuals do not work well when the outcome variable is discrete and ordered. A popular pseudo-R^2 measure due to McFadden (1973) is given by:

*R^2=1-\log{L_{fit}}/\log{L_0}*

where *\log{L_{fit}}* is the log-likelihood for the fitted model and *\log{L_0}* is the log-likelihood from an intercept only model that estimates the probability of each alternative to be the sample average. This function calculates this term for objects of class `oglmx`

.

1 | ```
McFaddensR2.oglmx(object)
``` |

`object` |
object of type |

numeric value between 0 and a theoretical maximum of 1.

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