implied.proportion: Function for calculating implied proportions.
In sumitrahman/perfman: Probability Estimates From Ordered Logistic Regression

Description Usage Arguments Details Value Examples

This utility function calcuates the implied proportions in the population for the specified outcome, making use of the probabilities for the various categories of the chosen variable and the chosen value of X.

1	implied.proportion(X, outcome, variable)

`X`	A real number. This is the number that is picking out one member of the family of probability functions that are consistent with the fitted logisitic model.
`outcome`	An integer specifying a particular outcome. This is one of the values of the outcome variable (i.e. the dependent variable from the model)
`variable`	A column name from the original data frame. This will be the variable one of whose values you are calculating the probability for.

The real-valued X indexes a family of probability distributions for a given explanatory variable. Since we know the distribution of the values of the chosen variable (from the original dataset, it is calculated in fit.model and stored in proportions.raw), this information is combined with the probability distributions for the different values of the variable to arrive at the implied probability for the chosen outcome.

For example, if we have a gender variable (taking values male and female), and in our dataset there are equal numbers of males and females, then the implied proportion for outcome 1 will be the mean of the male probability of outcome 1 and the female probability of outcome 1. If there were twice as many females as males, then the implied probability would be weighted towards the female probability twice as heavily as towards the male.

The calculated probability corresponding to the values you have specified.