Query regarding the experimental design and attribute levels

[CMA]

I am currently setting up the experimental design in the program.

Code: Select all

Design
;alts = alt1*, alt2*
;rows = 12
;eff = (mnl, d)
;alg = swap(stop = noimprov(3 mins))
;model:
U(alt1) = b1.dummy[-0.001|-0.002] * A[1, 2, 0]
        + b2.dummy[-0.001|-0.002] * B[1, 2, 0]
        + b3.dummy[-0.001|-0.002] * C[1, 2, 0]
        + b4.dummy[0|0]           * D[1, 2, 0]
        + b5[0.001]               * E[1, 2, 5, 10] ?life-year
        /
U(alt2) = b1 * A + b2 * B + b3 * C + b4 * D + b5 * E
$

Upon checking the life-year outcomes after a test run, I noticed that the comparisons seem limited: for instance, "1 year" is only compared with "10 years," and "2 years" is only compared with "5 years." Could you let me know if this is intended, or if there is an issue with the program logic?

I am concerned that only comparing 1 year with 10 years might be problematic. To resolve this and ensure a better distribution of comparisons, I am considering changing the structure to two blocks of 30 questions each.

In your opinion, which approach would be more appropriate for this experimental design?

Best regards,