Mixed Effects Models: A Conceptual Overview Using R

[@olearydj]

This is one of, if not the best video on the topic here on youtube. Very well done.

[@ifeanyionyekachi9800]

this is the best video i have ever came across that simplified the link between longitudinal data and mixed effect models. It is really helpful and thanks a lot for this video

[@jelenachuklina271]

absolutely fantastic overview of LMMs! Good balance of demonstrating many aspects of the model, tools, and of course, interpretation

[@janh7633]

Nice demonstration of testing competing models and of adding random intercepts and random intercepts & slopes

[@deniecewilliams1981]

This was very well presented and the explanations were easy to follow. Thank you. 😊

[@Sam-tg4ii]

Very clear. Thank you.

[@charleydublin7304]

Excellent presentation, thank you

[@jelenachuklina271]

I wonder, what is the demo tool you use, where you are able so elegantly to edit while doing the demo? :)

[@Sam-tg4ii]

6:05 But previously you said 5-6 groups is ideal for a variable used as random effect. But if you also say participants are used as random effect, isn't usually 100s of participants in a study? Doesn't that mean hundreds of groups in the random effect variable (participant ID)?

[@brianfisher6799]

I know this is slightly off topic, but maybe time of day when the sample was taken would account for a portion of that final unexplained variance.

[@PsychEDD]

Quite possible :)