Hi everyone, I have just started using NGENE, and choice modeling in general, so forgive me if any of my questions make little sense. I had a look in previous threads but I don’t know enough about the software to identify the issue I am having, which makes a solution hard to find.

I am working with data from a pilot test which included a stated choice component in which each “scenario” consisted of 5 attributes that were varied across different levels. After the data collection I developed a two in NLOGIT that had good fit r2=.333, but in order to get a good fitting model I had to recode the attributes into binary variables (technically I effects coded them).

Now I want to use the coefficients and standard errors these models to produce a design in NGENE. However, when I try to run my syntax NGENE shuts down (in the sense of crashing before I see an error message).

Since I am new to both choice modeling and NGENE I would appreciate any help in specifying what my problem is. I have a few potential candidates, presented with most likely at the top of the list.

1. Some basic issue with my syntax

2. The fact that I split the variables up into binary variables

3. The effects coding of the dummy variables

4. The assumption of normality

Sorry that the code looks a bit messy. I havn’t learned the finer points of the syntax yet, model1 is a MNL model and model2 is a RPM if that matters:

Design

;alts(model1) = alt1*, alt2*, alt3*

;alts(model2) = alt1*, alt2*, alt3*

;rows = 18

;block = 3

;eff = model1(mnl,d,mean)

;rep = 1000

;rdraws = gauss(3)

;bdraws = gauss(3)

;alg = swap(stop = noimprov(10000 iterations))

;model(model1):

U(alt1) = I1[(n,0.089,0.324) * A[-1,0,1] +I2[(n,0.132,0.247)] * A[-1,0,1] +W1[(n,0.161,0.184)] * A[-1,0,1] +W2[(n,1.233,0.235)] * A[-1,0,1] +H1[(n,0.3659,0.251)] * A[-1,0,1] +H2[(n,0.652,0.227)] * A[-1,0,1] +C1[(n,0.453,0.293)] * A[-1,0,1] +C2[(n,0.085,0.337)] * A[-1,0,1] +C3[(n,0.526,0.365)] * A[-1,0,1] +C4[(n,0.601,0.434)] * A[-1,0,1] +F1[(n,0.408,0.319)] * A[-1,0,1] +F2[(n,0.056,0.282)] * A[-1,0,1] +F3[(n,0.321,0.305)] * A[-1,0,1] +F4[(n,0.019,0.274)] * A[-1,0,1] /

U(alt2) = I1[(n,0.089,0.324) * A[-1,0,1] +I2[(n,0.132,0.247)] * A[-1,0,1] +W1[(n,0.161,0.184)] * A[-1,0,1] +W2[(n,1.233,0.235)] * A[-1,0,1] +H1[(n,0.3659,0.251)] * A[-1,0,1] +H2[(n,0.652,0.227)] * A[-1,0,1] +C1[(n,0.453,0.293)] * A[-1,0,1] +C2[(n,0.085,0.337)] * A[-1,0,1] +C3[(n,0.526,0.365)] * A[-1,0,1] +C4[(n,0.601,0.434)] * A[-1,0,1] +F1[(n,0.408,0.319)] * A[-1,0,1] +F2[(n,0.056,0.282)] * A[-1,0,1] +F3[(n,0.321,0.305)] * A[-1,0,1] +F4[(n,0.019,0.274)] * A[-1,0,1] /

U(alt3) = I1[(n,0.089,0.324) * A[-1,0,1] +I2[(n,0.132,0.247)] * A[-1,0,1] +W1[(n,0.161,0.184)] * A[-1,0,1] +W2[(n,1.233,0.235)] * A[-1,0,1] +H1[(n,0.3659,0.251)] * A[-1,0,1] +H2[(n,0.652,0.227)] * A[-1,0,1] +C1[(n,0.453,0.293)] * A[-1,0,1] +C2[(n,0.085,0.337)] * A[-1,0,1] +C3[(n,0.526,0.365)] * A[-1,0,1] +C4[(n,0.601,0.434)] * A[-1,0,1] +F1[(n,0.408,0.319)] * A[-1,0,1] +F2[(n,0.056,0.282)] * A[-1,0,1] +F3[(n,0.321,0.305)] * A[-1,0,1] +F4[(n,0.019,0.274)] * A[-1,0,1]

;model(model2):

U(alt1) = I1[(n,0.316,0.264)] * A[-1,0,1] + I2[(n,0.541,0.303)] * A[-1,0,1] + W1[(n,1.509,0.354)] * A[-1,0,1] + W2[(n,1.757,0.496)] * A[-1,0,1] + H1[(n,0.263,0.257)] * A[-1,0,1] + H2[(n,-1.924,0.524)] * A[-1,0,1] + C1[(n,2.648,0.693)] * A[-1,0,1] + C2[(n,-0.675,0.467)] * A[-1,0,1] + C3[(n,-0.122,0.526)] * A[-1,0,1] + C4[(n,-0.815,0.55)] * A[-1,0,1] + F1[(n,-2.821,0.788)] * A[-1,0,1] + F2[(n,-0.324,0.443)] * A[-1,0,1] + F3[(n,1.114,0.467)] * A[-1,0,1] + F4[(n,2.976,0.718)] * A[-1,0,1]/

U(alt2) = I1[(n,0.316,0.264)] * A[-1,0,1] + I2[(n,0.541,0.303)] * A[-1,0,1] + W1[(n,1.509,0.354)] * A[-1,0,1] + W2[(n,1.757,0.496)] * A[-1,0,1] + H1[(n,0.263,0.257)] * A[-1,0,1] + H2[(n,-1.924,0.524)] * A[-1,0,1] + C1[(n,2.648,0.693)] * A[-1,0,1] + C2[(n,-0.675,0.467)] * A[-1,0,1] + C3[(n,-0.122,0.526)] * A[-1,0,1] + C4[(n,-0.815,0.55)] * A[-1,0,1] + F1[(n,-2.821,0.788)] * A[-1,0,1] + F2[(n,-0.324,0.443)] * A[-1,0,1] + F3[(n,1.114,0.467)] * A[-1,0,1] + F4[(n,2.976,0.718)] * A[-1,0,1]/

U(alt3) = I1[(n,0.316,0.264)] * A[-1,0,1] + I2[(n,0.541,0.303)] * A[-1,0,1] + W1[(n,1.509,0.354)] * A[-1,0,1] + W2[(n,1.757,0.496)] * A[-1,0,1] + H1[(n,0.263,0.257)] * A[-1,0,1] + H2[(n,-1.924,0.524)] * A[-1,0,1] + C1[(n,2.648,0.693)] * A[-1,0,1] + C2[(n,-0.675,0.467)] * A[-1,0,1] + C3[(n,-0.122,0.526)] * A[-1,0,1] + C4[(n,-0.815,0.55)] * A[-1,0,1] + F1[(n,-2.821,0.788)] * A[-1,0,1] + F2[(n,-0.324,0.443)] * A[-1,0,1] + F3[(n,1.114,0.467)] * A[-1,0,1] + F4[(n,2.976,0.718)] * A[-1,0,1]

$

Thanks,

Max