Hello,
I would like to create an availability design. This type of design is often used when assessing the potential for new products entering a market. The availability design contains estimable cross effects, which are a useful way to remove the effect of IIA in logit models.
Here is a stylized example:
design
;alts = existing1, existing2, new, none
;eff=(mnl,d)
;model:
u(existing1) = b10 + b11*feature1_1[1,2,3] + b12*feature2_1[1,2,3] + b13*feature3_1[1,2,3,4] + ... /
u(existing2) = b20 + b21*feature1_2[1,2,3] + b22*feature2_2[1,2,3,4] + b23*feature3_2[1,2,3,4] + ... /
u(new) = b30 + b31*feature1_3[1,2,3] + b32*feature2_3[1,2,3,4] + b33*feature3_3[1,2,3,4] + ...
$
What is different here is that we want the "new" product to appear in the choice task only part of the time (say 8 times out of 12). So sometimes, there would be 4 choices available and sometimes only 3.
There are several ways to accomplish this.
Method 1: add an additional level to one attribute associated with "new". Treat that attribute as "not available" and zero out the full column when that attribute level comes up. With orthogonal designs, thsi generally works and all main effects are estimable, as are the availability cross effects. It helps to have an attribute avaialable with the right number of levels so that adding the extra one makes "not available" turn up the right number of itmes.
Method 2: add an additional attribute to "new" for availability. With orthogonal designs, we might give it levels 1, 2 and 3 where 1 and 2 are available and 3 is not, to create the desired imbalance. Or imbalance constraints could be used.
Metohd 3 (not generally recommended): add an additonal level to all attributes, with if-and-only-if constraints so that either all attributes are at the added level or none are. Generally, this doesn't provide the balance desired, so it's not so useful.
Ok, so this type of thing has been used with reasonable effect in orthogonal designs, where all priors are 0. But what about efficient designs with priors? How do you place a prior on "not available" since there's no actual parameter estimated for that? How do you place priors on the cross effects (if you have any)? And how would you implement this type of design in NGene?
Thanks much.
Paul