This is a simple fake data set to illustrate a logistic regression.

`fakeLogit`

A data frame with 10000 observations on the following 2 variables.

`x`

a five-item functionally ordered categorical variable

`y`

a binary variable that is either 0 or 1

The data are generated such that the outcome `y`

is a logistic
function of the `x`

variable and come from a `rbinom()`

call. The
estimated natural logged odds of `y`

when `x`

is 0 is -2.8. Each
unit increase in `x`

is simulated to increase the natural logged odds of
`y`

by 1.4. This example is very much patterned off a similar fake data
set that Pollock (2012) uses to teach about logistic regression. In his case,
`x`

is a stand-in for hypothetical education categories and `y`

is
whether this fake person voted or not.