Multinomial logistic regression is an important type of categorical data analysis. Specifically, it’s used when your response variable is nominal: more than two categories and not ordered.
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Logistic Regression
Member Training: Multinomial Logistic Regression
December 30th, 2022 by TAF Support
When Linear Models Don’t Fit Your Data, Now What?
June 20th, 2022 by Karen Grace-Martin
When your dependent variable is not continuous, unbounded, and measured on 
an interval or ratio scale, linear models don’t fit. The data just will not meet the assumptions of linear models. But there’s good news, other models exist for many types of dependent variables.
Today I’m going to go into more detail about 6 common types of dependent variables that are either discrete, bounded, or measured on a nominal or ordinal scale and the tests that work for them instead. Some are all of these.
Guidelines for writing up three types of odds ratios
December 6th, 2021 by Karen Grace-Martin
Odds ratios have a unique part to play in describing the effects of logistic regression models. But that doesn’t mean they’re easy to communicate to an audience who is likely to misinterpret them. So writing up your odds ratios has to be done with care. (more…)
Logistic Regression Analysis: Understanding Odds and Probability
November 22nd, 2021 by Karen Grace-Martin
Updated 11/22/2021
Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome.
People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent.
How Odds and Probability Differ
They measure the same thing on different scales. Imagine how confusing it would be if people used degrees Celsius and degrees Fahrenheit interchangeably. “It’s going to be 35 degrees today” could really make you dress the wrong way.
In measuring the likelihood of any outcome, we need to know (more…)
Member Training: Goodness of Fit Statistics
March 4th, 2021 by TAF Support
What are goodness of fit statistics? Is the definition the same for all types of statistical model? Do we run the same tests for all types of statistic model?
Member Training: Explaining Logistic Regression Results to Non-Researchers
August 1st, 2020 by TAF Support
Interpreting the results of logistic regression can be tricky, even for people who are familiar with performing different kinds of statistical analyses. How do we then share these results with non-researchers in a way that makes sense?