: You specify the "family" or distribution of your response variable (e.g., Poisson, Negative Binomial, or Gamma). The Systematic Component
The "work" of GENMOD involves specifying a (like Binomial or Poisson) and a link function that connects the data to the linear model. It is famously used for GEE (Generalized Estimating Equations) , a method used to analyze longitudinal data where measurements are taken from the same subjects repeatedly over time. genmod work
Handling Non-Normality: Traditional linear regression assumes that the response variable is normally distributed. Genmod removes this constraint, allowing for more accurate modeling of real-world data. : You specify the "family" or distribution of
margins, dydx(*) // average marginal effects margins exposure, at(x=1 2 3) estimates store model1 at(x=1 2 3) estimates store model1