Definitions
from Wiktionary, Creative Commons Attribution/ShareAlike License
 n. the inverse of the "sigmoid" or "logistic" function used in mathematics, especially in statistics. The logit of a number p between 0 and 1 is given by the formula:
Etymologies
Examples

· "logit" command: support multinomial logit via a new

CLARIFY uses statistical simulation often called “Monte Carlo” simulation to generate predicted values from a statistical model using any of the standard estimators: linear regression, logistic regression, ordered logit, etc.

More technically, we have estimated a statistical model using the ordered logit estimator with the following controls: age, gender, living in the South, education, marital status, having children, ethnicity (Latino), and race (African American).

If you know any statistics, the models are much easier to interpret, and with modern stats packages the algorithms are about as reliable and fast as logit.
Freeze  Statistics Police!, Bryan Caplan  EconLog  Library of Economics and Liberty

The author miscalculated the implied probabilities of his logit model.
Freeze  Statistics Police!, Bryan Caplan  EconLog  Library of Economics and Liberty

A seminal contribution by McFadden is his socalled conditional logit analysis.
The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 19692006

DV role playing scalar, not binary, so linear regression, not logit:

The author could have said, “If you run a logit regression with incidence of hypertension on the lefthand side and introduce a vector of control variables to control for potential contributory factors like age, SES, sex, etc. along with an indicator of whether the person is obese or not, the coefficient on the obesity indicator will be positive and statistically significant at the 5% confidence level.”

McFadden used it to develop his own multinomial logit model, a mathematical formula that assigns preference values to discrete choices for calculating the probability of each choice cf. discrete sets.

These developments, now called the multinomial logit model and the random utility model for choice behavior, have turned out to be widely useful in economics and other social sciences.
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