Multilevel models and Mixed Models are generally the same thing. In our recent webinar on the basics of mixed 
models, Random Intercept and Random Slope Models, we had a number of questions about terminology that I’m going to answer here.
If you want to see the full recording of the webinar, get it here. It’s free.
A: No. I don’t really know the history of why we have the different names, but the difference in multilevel modeling (more…)
What does it mean for two variables to be correlated?
Is that the same or different than if they’re associated or related?
This is the kind of question that can feel silly, but shouldn’t. It’s just a reflection of the confusing terminology used in statistics. In this case, the technical statistical term looks like, but is not exactly the same as, the way we mean it in everyday English. (more…)
The following statement might surprise you, but it’s true.
To run a linear model, you don’t need an outcome variable Y that’s normally distributed. Instead, you need a dependent variable that is:
The normality assumption is about the errors in the model, which have the same distribution as Y|X. It’s absolutely possible to have a skewed distribution of Y and a normal distribution of errors because of the effect of X. (more…)
What is a Confounder?
Confounder (also called confounding variable) is one of those statistical terms that confuses a lot of people. Not because it represents a confusing concept, but because of how it’s used.
(Well, it’s a bit of a confusing concept, but that’s not the worst part).
It has slightly different meanings to different types of researchers. The definition is essentially the same, but the research context can have specific implications for how that definition plays out.
If the person you’re talking to has a different understanding of what it means, you’re going to have a confusing conversation.
Let’s take a look at some examples to unpack this.
One of the key concepts in Survival Analysis is the Hazard Function.
But like a lot of concepts in Survival Analysis, the concept of “hazard” is similar, but not exactly the same as, its meaning in everyday English. Since it’s so important, though, let’s take a look. (more…)
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…)