Linear Mixed Models (LMM) - Lecture 9 - Data analysis using R

Описание: Learn about (multiple) linear mixed models, an extension of linear models that allow for both fixed and random effects. This lecture is an adaptation of the introductory tutorial for performing linear mixed effects analyses (Tutorial 2) by Bodo Winter (http://www.bodowinter.com/tutorial/bw.... We'll deal with random intercept and random slope models to model the voice pitch of individuals answering multiple questions.

Lectures: https://dannyarends.nl/rlectures/
Assignments and Answers: https://dannyarends.nl/r2022/
Playlist:    • Data analysis using R  

Chapters:
00:00:00 - Sound check and introduction
00:05:05 - Answers to Assignments Lecture 8
01:04:44 - Break 1: Tasmanian Devil gifs
01:11:06 - LMM Lecture Overview
01:14:59 - Why use Linear Mixed Models
01:20:05 - The Data Set used during the Lecture
01:22:04 - Building a basic linear model
01:23:56 - Introducing Random Effects
01:29:48 - LMMs in R using lmer
01:32:47 - Understanding the Output of a Linear Mixed Model
01:34:44 - Significance of Linear Mixed Model Predictor Variables
01:39:24 - Random Slopes versus Random Intercepts
01:45:56 - Lecture Overview
01:48:51 - Break 2: Honey Badger gifs
01:54:45 - Example: LMMs for QTL analysis in the Berlin Fat Mouse
02:38:02 - Questions and Outro

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