Description
Advanced course in models and methods for dependent data, an emphasis on non-normally distributed data. Topics include linear and generalized linear mixed models, logistic model for binary data, log-linear model for count data, marginal vs. conditional models, generalized estimating equation, missing data.
Prerequisites
- Prerequisite(s): Knowledge of simple regression analysis.
Conditions and arrangements
- Prerequisite(s): Knowledge of simple regression analysis.
Reference text in its original language
Advanced course in models and methods for dependent data, an emphasis on non-normally distributed data. Topics include linear and generalized linear mixed models, logistic model for binary data, log-linear model for count data, marginal vs. conditional models, generalized estimating equation, missing data.
- Prerequisite(s): Knowledge of simple regression analysis.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/grad/courses/STAT/