choice-metrics.com

Dear all,
I'm working on the design of a choice experiment with the following code:
Design
;alts=alt1, alt2, sq
;rows=12
;block=2
;eff=(mnl,d)
;model:
U(alt1) = b1.dummy[0|0]*ACT[2,3,1] + b2.dummy[0|0] * IMP[2,3,1]+ b3.dummy[0|0]* ACC[2,3,1]+ b4[-0.01]*PAY [0,75,150,225,300,375] /
U(alt2) = b1*ACT + b2*IMP + b3*ACC + b4*PAY /
U(SQ) = b6[0] + b4*PAYsq[0]

Considering the number of parameters to estimate, 12 choice sets seems to be a reasonable number. We are considering increasing the granularity of the payment attribute by increasing the number of levels to 12. Since the influence of payment will be estimated with only parameter, I assume that this does not change the number of parameter to estimate and we can stay with our 12 choice sets?
Could you confirm?
Thanks

Correct, changing the number of levels for a numerical attribute does not change the number of parameters and would not impact the design size. Using 12 rows would be sufficient, but I would probably increase the number of rows to get more variation in the data and trade-offs presented to respondents.