Linear Mixed Model in R with lme

Explore the concept of Linear Mixed Models (LMM) and learn how to implement them in R using the lme() function in this 26-minute tutorial. Dive into statistical modeling techniques, starting with simple linear models and progressing to more complex multivariate and general linear models. Understand how LMMs incorporate both fixed and random effects to prevent false negative correlations and misinterpretation of trends. Follow along with practical examples, including a glass tank experiment and dose-response curve analysis. Gain insights into pseudo-replication and random effects, and learn to interpret model outputs. Access accompanying resources, including R scripts on GitHub, presentation slides, and the original tutorial for further study. Enhance your data analysis skills and gain a deeper understanding of advanced statistical modeling techniques in bioinformatics.

Introduction
What is Statistical Modeling
Linear Modeling Example
Glass Tank Example
Dose Response Curve
Multivariant Model
General Linear Model
GLM Example
Linear Mix Model
Pseudo Replication
Random Effect
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output