See below. Yes zero priors is fine, although it is recommended to conduct a pilot study to get informative priors.
I assume that alt1 and alt2 are generic and that alt3 is an opt-out alternative.
When using zero priors, I found that it is usually best to dummy code all attributes, including numerical attribute cost.
Dominance checks cannot be performed if only one parameter has an indicated sign, so in your case you should use a zero prior for the cost coefficient.
Note that the last level is the base level when dummy coding.
Given your number of parameters, I would suggest increasing the number of rows while blocking the design.
Consider using more cost levels since they are far apart and the cost attribute may become dominant otherwise. For example, perhaps use 0, 500, 1000, 2000, 4000.
- Code: Select all
Design
;alts = alt1*, alt2*, optout
;rows = 24
;block = 2
;eff = (mnl, d)
;model:
U(alt1) = b1.dummy[0|0|0|0] * loc[1,2,3,4,0] ? 0=...[base], 1=..., 2=..., 3=..., 4=...
+ b2.dummy[0|0] * sup[1,2,0] ? 0=...[base], 1=..., 2=...
+ b3.dummy[0|0] * cost[500,4000,0]
+ b4.dummy[0] * lang[1,0] ? 0=...[base], 1=...
+ b5.dummy[0|0] * time[1,2,0] ? 0=...[base], 1=..., 2=...
/
U(alt2) = b1 * loc
+ b2 * sup
+ b3 * cost
+ b4 * lang
+ b5 * time
/
U(optout) = b6
$
Michiel
