Mixed Effects Models: A Conceptual Overview Using R
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- Опубліковано 6 лют 2025
- This is a bit of a seminar on mixed effects/ hierarchical / clustered models. I go over the difference between fixed effects vs random effects and how they work together in a single model. I cover variance components only models, random slopes and random intercepts.
00:00 a bit of background
07:57 the R stuff
Nice demonstration of testing competing models and of adding random intercepts and random intercepts & slopes
This is one of, if not the best video on the topic here on youtube. Very well done.
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
This was very well presented and the explanations were easy to follow. Thank you. 😊
absolutely fantastic overview of LMMs! Good balance of demonstrating many aspects of the model, tools, and of course, interpretation
Excellent presentation, thank you
Very clear. Thank you.
30:12 I'm getting a "singualr fit" for this model. Did I miss a step?
A likely cause is that your random effect explains close to zero variance
@@PsychEDD Thank you for the reply! I ran rePCA(model_5) and discovered that the "subjects" random effect was the source of the singularity. I simplified the model and the singularity warning went away: lmer(pitch ~ context + gender + (1|subject) + (1+context|sentence), data = politeness, REML = FALSE).
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)?
I wonder, what is the demo tool you use, where you are able so elegantly to edit while doing the demo? :)
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.
Quite possible :)
i like the voice. handsome one, hahaha