Generalized Linear Mixed Models (Vid 2)

[@ericknganzi398]

Thank you very much Prof Christina, your presentation is really amazing.

[@dc33333]

Very clear!!!!

[@checkle1]

that last slide should have been shown first! but thanks for this!

[@catalinastats]

Thank you SO much!!!!

[@Sami-Moon]

this is great thank you.

[@dnsfloren]

thanks for this!

[@workfromhome1453]

Thanks for the video! I also have a question on the 10th slide where you wrote log(mu_hat) = beta0+u_1*I(Christina)+.....+u_30*I(Becca). I think your original equation is correct log(mu) = beta0+u_1*I(Christina)+.....+u_30*I(Becca) (No hat above the mu) because g(E(y)) = x*beta according to GLM definition, and E(y) = mu not mu hat.