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Master CDA and GLM applications
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Module 11
Poisson Regression and Log-Linear Models
1
Poisson Regression: Modeling Counts and Interpreting the Log Link
Formulate a Poisson regression model for count data and explain the interpretation of the log link function.
2
Interpreting and Converting Poisson Regression Coefficients
Interpret Poisson regression coefficients as log rate ratios and convert them to rate ratios.
3
Understanding and Detecting Overdispersion
Explain the issue of overdispersion, its consequences for inference, and how to detect it.
4
Log-Linear Models for Contingency Tables
Describe how log-linear models represent association structures in contingency tables.
5
Chi-Square Test and Saturated Log-Linear Models
Explain the relationship between the chi-square test of independence and the saturated log-linear model.
6
Poisson Regression and Log-Linear Models: A Unified Approach
Connect the concepts of Poisson regression and log-linear models.
7
Log-Linear Models for Multi-Way Tables
Apply a log-linear model to a multi-way contingency table to interpret its association structure.
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