Regression is one of the most common analyses in statistics. Most of us learn it in grad school, and we learned it in a specific software. Maybe SPSS, maybe another software package. The thing is, depending on your training and when you did it, there is SO MUCH to know about doing a regression analysis in SPSS.
Regression models
Member Training: Linear Regression in SPSS (Tutorial)
March 29th, 2024 by Kat Caldwell
Assumptions of Linear Models are about Errors, not the Response Variable
March 19th, 2024 by Karen Grace-Martin
I recently received a great question in a comment about whether the assumptions of normality, constant variance, and independence in linear models are about the errors, εi, or the response variable, Yi.
The asker had a situation where Y, the response, was not normally distributed, but the residuals were.
Quick Answer: It’s just the errors.
In fact, if you look at any (good) statistics textbook on linear models, you’ll see below the model, stating the assumptions: (more…)
Beyond R-squared: Assessing the Fit of Regression Models
February 20th, 2024 by Karen Grace-Martin
A well-fitting regression model results in predicted values close to the observed data values. The mean model, which uses the mean for every predicted value, generally would be used if there were no useful predictor variables. The fit of a proposed regression model should therefore be better than the fit of the mean model. But how do you measure that model fit?
Five Ways to Analyze Ordinal Variables (Some Better than Others)
December 3rd, 2023 by Karen Grace-Martin
There are not a lot of statistical methods designed just to analyze ordinal variables.
But that doesn’t mean that you’re stuck with few options. There are more than you’d think.
Some are better than others, but it depends on the situation and research questions.
Here are five options when your dependent variable is ordinal.
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Concepts in Linear Regression to know before learning Multilevel Models
November 21st, 2023 by Karen Grace-Martin
Are you learning Multilevel Models? Do you feel ready? Or in over your head?
It’s a very common analysis to need to use. I have to say, learning it is not so easy on your own. The concepts of random effects are hard to wrap your head around and there is a ton of new vocabulary and notation. Sadly, this vocabulary and notation is not consistent across articles, books, and software, so you end up having to do a lot of translating.
Member Training: Linear Model Assumption Violations: What’s Next?
June 30th, 2023 by guest contributer
What do you do if the assumptions of linear models are violated?
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