I am conducting a DCE to elicit preferences for a neurodevelopmental follow-up care for children in Australia. I am currently doing a pilot study mainly to check the survey functionality and obtain priors for the main DCE study. I have 2 alternatives and an opt-out.
I have the following seven attributes: location (levels 0, 1, 2), modality (levels 0, 1, 2), cost (levels 0, 1, 2, 3, 4), mental health support (levels 0, 1), education (levels 0, 1, 2, 3, 4), managing appointments (levels 0, 1), and waiting time (levels 0, 1, 2). I have dummy coded all the levels.
I have some constraints on the design:
• If location is 0, cost can only be 0 or 1.
• If location is 1 and 2, cost can be 1, 2, 3, or 4.
I was able to run the design in NGENE using the codes pasted below; however, I observed:
• When I used 20 (2 blocks) and 30 rows (3 blocks), there were no level overlaps in any of the attributes.
• When I used 40 (4 blocks) and 50 rows (5 blocks), there level overlaps few times in location and cost attributes (without me imposing any overlap constraint).
I am not sure why this was happening? I ended up selecting the design with 30 rows even though the d-error for 40 and 50 rows was better. But I did not want any overlaps in the design.
Are there any other suggestions to improve my design?
- Code: Select all
Design
;alts = optA*, optB*, optout
;rows = 30
;block = 3
;eff = (mnl,d)
;cond:
if (optA.location = 0, optA.cost = [0,1]),
if (optB.location = 0, optB.cost = [0,1]),
if (optA.location = [1,2], optA.cost = [1,2,3,4]),
if (optB.location = [1,2], optB.cost = [1,2,3,4])
;model:
U(optA) = b1.dummy[0.000001 | 0.000002] * location[0, 1, 2]
+ b2.dummy[0.000001 | 0.000002] * modality[0, 1, 2]
+ b3.dummy[0.000001 | 0.000002 | 0.000003 | 0.000004] * cost[0, 1, 2, 3, 4]
+ b4.dummy[0.000001] * mentalhealth[0, 1]
+ b5.dummy[0.000001 | 0.000002 | 0.000003 | 0.000004] * education[0, 1, 2, 3, 4]
+ b6.dummy[0.000001] * appointments[0, 1]
+ b7.dummy[0.000001 | 0.000002] * waiting[0, 1, 2]
/
U(optB) = b1 * location
+ b2 * modality
+ b3 * cost
+ b4 * mentalhealth
+ b5 * education
+ b6 * appointments
+ b7 * waiting
$
Thanks very much in advance.
Kind regards,
Pakhi