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GLM - 13 - GEE (Generalized Estimating Equations)

When we're dealing with data coming in groups, GEE extends the GLM likelihood analysis to incorporate a (within group) correlation structure. There are different (plausible) correlation structures: independence, exchangeable, autoregressive, etc. for different scenarios. The correlation structure is estimated by averaging on the Pearson's residuals. The estimation is done in an iterative way - estimate the coefficients, then the correlations, rinse-repeat. Corrections: * At 03:00 - Panel data is actually a synonym for longitudinal data. * At 8:30 - under-estimation and over-estimation is of-course assuming that rho is positive. If rho is negative the under and over are switched. Become a member and get full access to this online course: https://meerkatstatistics.com/courses... * 🎉 Special YouTube 60% Discount on Yearly Plan – valid for the 1st 100 subscribers; Voucher code: First100 🎉 * “GLM in R” Course Outline: Administration * Administration Up to Scratch * Notebook – Introduction * Notebook – Linear Models * Notebook – Intro to R Intro to GLM’s * Linear Models vs. Generalized Linear Models * Least Squares vs. Maximum Likelihood * Saturated vs. Constrained Model * Link Functions Exponential Family * Definition and Examples * More Examples * Notebook – Exponential Family * Mean and Variance * Notebook – Mean-Variance Relationship Deviance * Deviance * Notebook – Deviance Likelihood Analysis * Likelihood Analysis * Numerical Solution * Notebook – GLM’s in R * Notebook – Fitting the GLM * Inference Code Examples: * Notebook – Binary/Binomial Regression * Notebook – Poisson & Negative Binomial Regression * Notebook – Gamma & Inverse Gaussian Regression Advanced Topics: * Quasi-Likelihood * Generalized Estimating Equations (GEE) * Mixed Models (GLMM) Why become a member? * All video content * Extra material (notebooks) * Access to code and notes * Community Discussion * No Ads * Support the Creator ❤️ GLM (restricted) playlist: https://bit.ly/2ZMSv4U If you’re looking for statistical consultation, someone to work on interesting projects, or training workshops, visit my website https://meerkatstatistics.com/ or contact me directly at [email protected] ~~~~~ SUPPORT ~~~~~ Paypal me: https://paypal.me/MeerkatStatistics ~~~~~~~~~~~~~~~~~ Liang and Zeger paper: https://bit.ly/3zPF2cA Hardin and Hilbe book: https://amzn.to/3rGgShG Agresti book: https://bit.ly/2V9SB7x