When analyzing longitudinal data, do you use regression or structural equation based approaches? There are many types of longitudinal data and different approaches to analyzing them. Two popular approaches are a regression based approach and a structural equation modeling based approach.
linear regression
Member Training: Analyzing Longitudinal Data: Comparing Regression and Structural Equation Modeling Approaches
July 2nd, 2024 by TAF SupportMember Training: Linear Regression in SPSS (Tutorial)
March 29th, 2024 by Kat Caldwell
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.
Member Training: The Link Between ANOVA and Regression
January 31st, 2023 by TAF SupportIf you’ve used much analysis of variance (ANOVA), you’ve probably heard that ANOVA is a special case of linear regression. Unless you’ve seen why, though, that may not make a lot of sense. After all, ANOVA compares means between categories, while regression predicts outcomes with numeric variables.
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Can Likert Scale Data ever be Continuous?
January 19th, 2023 by Karen Grace-MartinA very common question is whether it is legitimate to use Likert scale data in parametric statistical procedures that 
require interval data, such as Linear Regression, ANOVA, and Factor Analysis.
A typical Likert scale item has 5 to 11 points that indicate the degree of something. For example, it could measure agreement with a statement, such as 1=Strongly Disagree to 5=Strongly Agree. It can be a 1 to 5 scale, 0 to 10, etc. (more…)
Member Training: Centering
November 30th, 2022 by TAF SupportCentering variables is common practice in some areas, and rarely seen in others. That being the case, it isn’t always clear what are the reasons for centering variables. 
Is it only a matter of preference, or does centering variables help with analysis and interpretation? (more…)
The Difference Between R-squared and Adjusted R-squared
August 22nd, 2022 by Karen Grace-MartinWhen is it important to use adjusted R-squared instead of R-squared?
R², the the Coefficient of Determination, is one of the most useful and intuitive statistics we have in linear regression.
It tells you how well the model predicts the outcome and has some nice properties. But it also has one big drawback.