Bayesian efficient design and status quo option
Posted: Wed Jul 11, 2018 8:40 pm
Good day,
I want to generate an unlabeled design with 2 alternatives and a status quo option. Attribute D is the price attribute and I would like constraint it to > 0 for alt1 and alt2. The status quo option has specified levels which should be fixed/constant for all choice tasks.
I run the syntax below but the constraints were not obeyed. There were still 0 attribute levels in alt1 and alt2, and the sq option varied.
Question:
1. Is the syntax below correct?
2. Should I rather remove the status quo option in the model specification and introduce ASC in alt1 and alt2 (in the model specification). Which is better?
Thank you in advance for your assistance.
Best regards,
Linda
I want to generate an unlabeled design with 2 alternatives and a status quo option. Attribute D is the price attribute and I would like constraint it to > 0 for alt1 and alt2. The status quo option has specified levels which should be fixed/constant for all choice tasks.
I run the syntax below but the constraints were not obeyed. There were still 0 attribute levels in alt1 and alt2, and the sq option varied.
Question:
1. Is the syntax below correct?
2. Should I rather remove the status quo option in the model specification and introduce ASC in alt1 and alt2 (in the model specification). Which is better?
- Code: Select all
Design;
;alts = alt1, alt2, sq
;rows = 12
;eff = (mnl,d,mean)
;bdraws = gauss(1)
;require:
alt1.D > 0,
alt2.D > 0,
sq.A = 0 and sq.B = 12 and sq.C = 2500 and sq.D = 0
;model:
U(alt1) = b2.dummy[(n,0.168138,0.085785)|(n,0.336276,0.085785)] * A[0,1,2] + b3[(n,0.028023,0.007149)] * B[8,12,16] + b4[(n,0.000028,0.114365)] * C[1000,2500,5000,7500] + b5[(n,-0.011209,0)] * D[0,10,20,40,80,120]/
U(alt2) = b2 * A + b3 * B + b4 * C + b5 * D /
U(sq) = b2 * A + b3 * B + b4 * C + b5 * D
$
Thank you in advance for your assistance.
Best regards,
Linda