This might have a very obvious answer, but I have written code that should be searching for a d-optimal choice experiment design with three alternatives, where the third alternative is the status quo option. The number of rows and blocks is given by one of the suggested designs generated in SAS using %mktruns.
There is one 4-level attribute (quantitative), one 3-level attribute (quantitative); and two qualitative variables of 2 and 3 levels respectively.
The algorithm will not stop evaluating designs. Do I need to specify a maximum number of iterations, or a tolerance for the d-error?
Thank you in advance. The code is below:
- Code: Select all
Design
;alts = alt1, alt2, alt3
;rows=12
;block=4
;eff=(mnl,d)
;model:
U(alt1) = cost[0]*cost[1,3,7,10] + program.dummy[0|0]*program[1,2,3] + level.dummy[0]*level[1,2] + time[0]*time[10,20,50]/
U(alt2) = cost[0]*cost[1,3,7,10] + program.dummy[0|0]*program[1,2,3] + level.dummy[0]*level[1,2] + time[0]*time[10,20,50]/
U(alt3)= asc
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