Linear modeling in R using categorical variables - parallel slopes models

Need to include a categorical variable in your linear model in R? Start here.
If this vid helps you, please help me a tiny bit by mashing that 'like' button. For more #rstats joy, crush that 'subscribe' button!

[@EquitableEquations]

You can find materials for this vid (and others) at github.com/equitable-equations/youtube.

[@jayskieeee]

Thank you so much for the crystal clear explanation kind sir

[@marcosdanieldasilva5127]

Great video. I from Brazil and I have a question: I read in a book about some tests comparing regression models with qualitative variables through parallelism tests, regression equivalence tests, and identity tests. What I want to know is if it's possible to unite groups, for example group A == B, A != C, by creating a model y ~ 1 + x + dummy, where dummy is (AB and C).

[@romanvasiura6705]

Thank you!

[@Dilysia21]

Hi, your videos have been helpful. Can you please share your notes or where can I find them?

[@EquitableEquations]

Hi! I've been working on this backlog - thanks for your patience. You can now find these materials on my GitHub: github.com/equitable-equations/youtube.

[@andreasschmidt186]

Hello, what can i do when i have 3 categorical independent variables with 2, 3 and 4 levels?

[@EquitableEquations]

Hi! The most direct thing to do is to encode each level of each category with a 1 or 0. So you’d have 9 binary explanatory variables in your example. This is sometimes called “one hot encoding.”

[@EquitableEquations]

I’m planning a vid on this some time in 2022. Stay tuned!