If 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. [Read more…] about Member Training: The Link Between ANOVA and Regression
The Difference Between Link Functions and Data Transformations
Generalized linear models—and generalized linear mixed models—are called generalized linear because they connect a model’s outcome to its predictors in a linear way. The function used to make this connection is called a link function. Link functions sounds like an exotic term, but they’re actually much simpler than they sound.
For example, Poisson regression (commonly used for outcomes that are counts) makes use of a natural log link function as follows:
[Read more…] about The Difference Between Link Functions and Data Transformations
Member Training: Generalized Linear Models
Using Pairwise Comparisons to Help you Interpret Interactions in Linear Regression
In a previous post we discussed using marginal means to explain an interaction to a non-statistical audience. The output from a linear regression model can be a bit confusing. This is the model that was shown.
In this model, BMI is the outcome variable and there are three predictors:
[Read more…] about Using Pairwise Comparisons to Help you Interpret Interactions in Linear Regression
What Are Nested Models?
Pretty much all of the common statistical models we use, with the exception of OLS Linear Models, use Maximum Likelihood estimation.
This includes favorites like:
- All Generalized Linear Models, including logistic, probit, beta, Poisson, negative binomial regression
- Linear Mixed Models
- Generalized Linear Mixed Models
- Parametric Survival Analysis models, like Weibull models
- Structural Equation Models
That’s a lot of models.
If you’ve ever learned any of these, you’ve heard that some of the statistics that compare model fit in competing models require [Read more…] about What Are Nested Models?
Incorporating Graphs in Regression Diagnostics with Stata
You put a lot of work into preparing and cleaning your data. Running the model is the moment of excitement.
You look at your tables and interpret the results. But first you remember that one or more variables had a few outliers. Did these outliers impact your results? [Read more…] about Incorporating Graphs in Regression Diagnostics with Stata