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?
Regression models
Member Training: Explaining Logistic Regression Results to Non-Researchers
August 1st, 2020 by TAF Support
Simplifying a Categorical Predictor in Regression Models
January 14th, 2020 by Jeff Meyer
One of the many decisions you have to make when model building is which form each predictor variable should take. One specific version of this
decision is whether to combine categories of a categorical predictor.
The greater the number of parameter estimates in a model the greater the number of observations that are needed to keep power constant. The parameter estimates in a linear (more…)
Same Statistical Models, Different (and Confusing) Output Terms
January 7th, 2020 by Jeff Meyer
Learning how to analyze data can be frustrating at times. Why do statistical software companies have to add to our confusion?
I do not have a good answer to that question. What I will do is show examples. In upcoming blog posts, I will explain what each output means and how they are used in a model.
We will focus on ANOVA and linear regression models using SPSS and Stata software. As you will see, the biggest differences are not across software, but across procedures in the same software.
Confusing Statistical Term #8: Odds
December 10th, 2019 by Karen Grace-Martin
Odds is confusing in a different way than some of the other terms in this series.
First, it’s a bit of an abstract concept, which I’ll explain below.
But beyond that, it’s confusing because it is used in everyday English as a synonym for probability, but it’s actually a distinct technical term.
I found this incorrect definition recently in a (non-statistics) book: (more…)
What is Multicollinearity? A Visual Description
November 20th, 2019 by Karen Grace-Martin
Multicollinearity is one of those terms in statistics that is often defined in one of two ways:
1. Very mathematical terms that make no sense — I mean, what is a linear combination anyway?
2. Completely oversimplified in order to avoid the mathematical terms — it’s a high correlation, right?
So what is it really? In English?
Member Training: Practical Advice for Establishing Reliability and Validity
October 30th, 2019 by guest contributer
How do you know your variables are measuring what you think they are? And how do you know they’re doing it well?
A key part of answering these questions is establishing reliability and validity of the measurements that you use in your research study. But the process of establishing reliability and validity is confusing. There are a dizzying number of choices available to you.