Hello,
Thank you for providing this discussion forum. I have found it and the Ngene documentation very useful. I am trying to create what I think is a simple experimental design consisting of 4 attributes, 2 of which are dummies. When I use the following syntax:
Design
;alts = alt1*, alt2*, alt3
;rows = 12
;eff = (mnl,d)
;alg = mfederov
;model:
U(alt1) = b2[-0.1] * PRICE[0.89,1.19,1.49] + b3.dummy[0] * BOTTLE[0,1] +
b4.dummy[0] * PROD[0,1] + b5[-0.0001] * CF[50,500,1000] /
U(alt2) = b2 * PRICE + b3.dummy * BOTTLE + b4.dummy * PROD + b5 * CF
$
I get reasonable results. After a few minutes it finds a design with an S estimate of 186 and everything looks reasonable. However, if I remove 'alt3' from the list of alternatives, I get much worse results, with an S estimate greater than 1000 after a few minutes.
Why is the presence of alt3, the no-choice option with no utility function, so critical to the outcome?
Also, I am interested in running experiments without a no-choice alternative, so I tried running the following:
Design
;alts = alt1*, alt2*, alt3*
;rows = 12
;eff = (mnl,d)
;alg = mfederov
;model:
U(alt1) = b2[-0.1] * PRICE[0.89,1.19,1.49] + b3.dummy[0] * BOTTLE[0,1] +
b4.dummy[0] * PROD[0,1] + b5[-0.0001] * CF[50,500,1000] /
U(alt2) = b2 * PRICE + b3.dummy * BOTTLE + b4.dummy * PROD + b5 * CF /
U(alt3) = b2 * PRICE + b3.dummy * BOTTLE + b4.dummy * PROD + b5 * CF
$
This causes Ngene to crash every time. Any help on what's going on would be much appreciated!
-steve