logit

How to Decide Between Multinomial and Ordinal Logistic Regression Models

March 11th, 2019 by

A great tool to have in your statistical tool belt is logistic regression.

It comes in many varieties and many of us are familiar with the variety for binary outcomes.

But multinomial and ordinal varieties of logistic regression are also incredibly useful and worth knowing.

They can be tricky to decide between in practice, however.  In some — but not all — situations you (more…)


Link Functions and Errors in Logistic Regression

March 14th, 2018 by

I recently held a free webinar in our The Craft of Statistical Analysis program about Binary, Ordinal, and Nominal Logistic Regression.

It was a record crowd and we didn’t get through everyone’s questions, so I’m answering some here on the site. They’re grouped by topic, and you will probably get more out of it if you watch the webinar recording. It’s free.

The following questions refer to this logistic regression model: (more…)


What is a Logit Function and Why Use Logistic Regression?

May 11th, 2015 by

One of the big assumptions of linear models is that the residuals are normally distributed.  This doesn’t mean that Y, the response variable, has to also be normally distributed, but it does have to be continuous, unbounded and measured on an interval or ratio scale.

Unfortunately, categorical response variables are none of these. (more…)