018. Linear Mixed Effects Models

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In this video we introduce, in full, mixed effect models for continuous outcomes. We discuss the specific (common) situations of random intercept and random slope models, and discuss how these generalize beyond. We discuss how we estimate parameters, conduct inference, and test hypothesis. We also spend some time detailing individual level prediction with BLUPs.

Video Timeline
00:00 - Introduction
01:22 - Linear Mixed Effects Models
06:11 - Distributions of Random Effects Terms
16:47 - Specific Examples
22:59 - Estimation and Hypothesis Testing
26:03 - Response Predictions (BLUPs)
30:45 - Summary and Conclusions
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this is awesome, I love your teaching style 💜

lorenzoplaserrano
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Very nice video lectures, thank you for making them available!

On the mean, variance, and distribution slide (at 14.48) should the expectations E[Yi | bi] and E[Yi] be written as E[Yi | bi, Xi] and E[Yi | Xi], respectively?

tomth