MarginalEffectsParameterCalc Class

Marginal effects are use a logistic regression model to predict how changing the value of a predictor, or covariate, effects the predicted outcome. It is the slope of the regression surface with respect to a given covariate and communicates the rate at which the outcome computed by the regression model changes at a given point in covariate space, with respect to one covariate dimension and holding all covariate values constant. Marginal effects for categorical covariates, including binary covariates, are straightforward - it is simply the difference in the predicted outcomes as the the design or dummy variable's value changes from 0 to 1. For continuous valued covariates it is the derivate dy/dx where y is the models prediction function and x is the covariate we are computing the marginal effects for. Note that the marginal effect for a predictor is computed at specific observation.

public class MarginalEffects<ParameterCalc>
where ParameterCalc : new(), ILogisticRegressionCalc

Public Class MarginalEffects(Of ParameterCalc As {New, ILogisticRegressionCalc})

generic<typename ParameterCalc>
where ParameterCalc : gcnew(), ILogisticRegressionCalc
public ref class MarginalEffects

type MarginalEffects<'ParameterCalc when 'ParameterCalc : new() and ILogisticRegressionCalc> = class end