marginaleffect
Marginal effect refers to the change in the predicted value of a dependent variable associated with a one-unit change in an independent variable, holding other variables constant. It is used to summarize how small changes in inputs influence outputs, and it can apply to continuous predictors or to discrete changes in binary indicators. For continuous variables, the marginal effect is typically the partial derivative of the expected outcome with respect to the variable. For binary indicators, it often represents the discrete change in the predicted outcome when the variable switches from 0 to 1, evaluated at fixed values of the other covariates.
In linear models, marginal effects are straightforward: they equal the regression coefficients and are constant across
Calculation typically involves differentiating the model’s predicted outcome with respect to the variable of interest. If