Dear Michiel!
I would like to create a D-efficient design for three unlabelled alternatives.
I used the following syntax in Ngene:
design
;alts = alt1, alt2, alt3
;rows = 16
;block = 2
;eff = (mnl,d)
;con
;model:
U(alt1) = a1[0.001] + b2[-0.001] * price[10,18,26,30] + b3[-0.001] * invcost[200,300,700,1000] + b4[0.001] * env[1,2,3,4] + b5.dummy[-0.001] * conv[0,1] /
U(alt2) = a2[0.001] + b2*price + b3*invcost + b4*env + b5*conv /
U(alt3) = b2*price + b3*invcost + b4*env + b5*conv
$
I got the following results:
D error 0.009803
A error 0.180855
B estimate 86.613607
S estimate 1511311.361419
Is it possible to got that very large S estimate result (It can be caused by my relatively small prior values?)?
Furthermore in my results I found two problematistic choice tasks (due to dominant alternatives).
What is the best way/practice what I can do with these choice tasks?
Thank you very much for you answer!
Best regards,
Peter