Specification of membership model

[ASINDU MARSY]

Dear Prof. Bierlaire,

I am running a latent class model with two classes and includes a membership model with three socio-economic variables(income, distance, and age). In the biogeme file labelled 16panelDiscreteSocioEco.py you offer an example of introducing social economic variables in a latent class model with 2 classes, the example provided involves only one socio-economic variable (Income) as shown in the class membership model below;

 W = CLASS_CTE + CLASS_INC * INCOME

PROB_class0 = models.logit({0: W, 1: 0}, None, 0)

PROB_class1 = models.logit({0: W, 1: 0}, None, 1)

 

In my situation with three socio-economic variables(income, distance and age), what would be the rightfull specification (A or B) in the examples below. And in case both specifications are incorrect, what would be the correct specification. 

Approach A         C = CLASS_CTE + CLASS_INC * income

                              PROB_class0 = models.logit({0: C, 1: 0}, None, 0)

                              PROB_class1 = models.logit({0: C, 1: 0}, None, 1)

 

                              D = CLASS_CTE + CLASS_INC * distance

                               PROB_class0 = models.logit({0: D, 1: 0}, None, 0)

                               PROB_class1 = models.logit({0: D, 1: 0}, None, 1)

 

                              E = CLASS_CTE + CLASS_INC * age

                               PROB_class0 = models.logit({0: E, 1: 0}, None, 0)

                               PROB_class1 = models.logit({0: E, 1: 0}, None, 1)

 

Approach B        

                              W = CLASS_CTE + CLASS_INC * income * distance * age

                              PROB_class0 = models.logit({0: W, 1: 0}, None, 0)

                               PROB_class1 = models.logit({0: W, 1: 0}, None, 1)

 

Many thanks in advance for your kind support

Best regards,