I would like prevent no more than 4 attributes from varying between alternatives. I am using the code at (viewtopic.php?f=4&t=525)
I've created a set of 10000 choice sets that meet this criteria (https://drive.google.com/file/d/19Uj6Tq ... sp=sharing)
When I run my code I get "MNL D-Error Undefined." All designs are invalid.
I was hoping on get help on getting this strategy to work, or an alternative strategy?
Thank you.
- Code: Select all
Design
;alts(not_used) = alt1, alt2
;alts(main) = alt1, alt2
;rows = 120
;eff = main(mnl, d)
;block=10
;alg=mfederov(candidates=profiles_may13.csv)
;model(not_used):
U(alt1) = b1[0.76]*time[10,5,2,1] +
b2.dummy[0|0|0|0]*se[0,1,2,3,4] +
ise1[-0.02]*se.dummy[1]*time +
ise2[-0.04]*se.dummy[2]*time +
ise3[-0.06]*se.dummy[3]*time +
ise4[-0.08]*se.dummy[4]*time +
b3.dummy[0|0|0|0]*l[0,1,2,3,4] +
il1[-0.02]*l.dummy[1]*time +
il2[-0.04]*l.dummy[2]*time +
il3[-0.06]*l.dummy[3]*time +
il4[-0.08]*l.dummy[4]*time +
b4.dummy[0|0|0|0]*a[0,1,2,3,4] +
ia1[-0.02]*a.dummy[1]*time +
ia2[-0.04]*a.dummy[2]*time +
ia3[-0.06]*a.dummy[3]*time +
ia4[-0.08]*a.dummy[4]*time +
b5.dummy[0|0|0|0]*bo[0,1,2,3,4] +
ibo1[-0.02]*bo.dummy[1]*time +
ibo2[-0.04]*bo.dummy[2]*time +
ibo3[-0.06]*bo.dummy[3]*time +
ibo4[-0.08]*bo.dummy[4]*time +
b6.dummy[0|0|0|0]*bl[0,1,2,3,4] +
ibl1[-0.02]*bl.dummy[1]*time +
ibl2[-0.04]*bl.dummy[2]*time +
ibl3[-0.06]*bl.dummy[3]*time +
ibl4[-0.08]*bl.dummy[4]*time +
b7.dummy[0|0|0|0]*p[0,1,2,3,4] +
ip1[-0.02]*p.dummy[1]*time +
ip2[-0.04]*p.dummy[2]*time +
ip3[-0.06]*p.dummy[3]*time +
ip4[-0.08]*p.dummy[4]*time +
b8.dummy[0|0|0|0]*m[0,1,2,3,4] +
im1[-0.02]*m.dummy[1]*time +
im2[-0.04]*m.dummy[2]*time +
im3[-0.06]*m.dummy[3]*time +
im4[-0.08]*m.dummy[4]*time +
b9.dummy[0|0|0|0]*so[0,1,2,3,4] +
iso1[-0.02]*so.dummy[1]*time +
iso2[-0.04]*so.dummy[2]*time +
iso3[-0.06]*so.dummy[3]*time +
iso4[-0.08]*so.dummy[4]*time /
U(alt2) = b1*time +
b2.dummy*se +
ise1*se.dummy[1]*time +
ise2*se.dummy[2]*time +
ise3*se.dummy[3]*time +
ise4*se.dummy[4]*time +
b3.dummy*l +
il1*l.dummy[1]*time +
il2*l.dummy[2]*time +
il3*l.dummy[3]*time +
il4*l.dummy[4]*time +
b4.dummy*a +
ia1*a.dummy[1]*time +
ia2*a.dummy[2]*time +
ia3*a.dummy[3]*time +
ia4*a.dummy[4]*time +
b5.dummy*bo +
ibo1*bo.dummy[1]*time +
ibo2*bo.dummy[2]*time +
ibo3*bo.dummy[3]*time +
ibo4*bo.dummy[4]*time +
b6.dummy*bl +
ibl1*bl.dummy[1]*time +
ibl2*bl.dummy[2]*time +
ibl3*bl.dummy[3]*time +
ibl4*bl.dummy[4]*time +
b7.dummy*p +
ip1*p.dummy[1]*time +
ip2*p.dummy[2]*time +
ip3*p.dummy[3]*time +
ip4*p.dummy[4]*time +
b8.dummy*m +
im1*m.dummy[1]*time +
im2*m.dummy[2]*time +
im3*m.dummy[3]*time +
im4*m.dummy[4]*time +
b9.dummy*so +
iso1*so.dummy[1]*time +
iso2*so.dummy[2]*time +
iso3*so.dummy[3]*time +
iso4*so.dummy[4]*time
;model(main):
U(alt1) =
ise1[-0.02]*se.dummy[1]*time +
ise2[-0.04]*se.dummy[2]*time +
ise3[-0.06]*se.dummy[3]*time +
ise4[-0.08]*se.dummy[4]*time +
il1[-0.02]*l.dummy[1]*time +
il2[-0.04]*l.dummy[2]*time +
il3[-0.06]*l.dummy[3]*time +
il4[-0.08]*l.dummy[4]*time +
ia1[-0.02]*a.dummy[1]*time +
ia2[-0.04]*a.dummy[2]*time +
ia3[-0.06]*a.dummy[3]*time +
ia4[-0.08]*a.dummy[4]*time +
ibo1[-0.02]*bo.dummy[1]*time +
ibo2[-0.04]*bo.dummy[2]*time +
ibo3[-0.06]*bo.dummy[3]*time +
ibo4[-0.08]*bo.dummy[4]*time +
ibl1[-0.02]*bl.dummy[1]*time +
ibl2[-0.04]*bl.dummy[2]*time +
ibl3[-0.06]*bl.dummy[3]*time +
ibl4[-0.08]*bl.dummy[4]*time +
ip1[-0.02]*p.dummy[1]*time +
ip2[-0.04]*p.dummy[2]*time +
ip3[-0.06]*p.dummy[3]*time +
ip4[-0.08]*p.dummy[4]*time +
im1[-0.02]*m.dummy[1]*time +
im2[-0.04]*m.dummy[2]*time +
im3[-0.06]*m.dummy[3]*time +
im4[-0.08]*m.dummy[4]*time +
iso1[-0.02]*so.dummy[1]*time +
iso2[-0.04]*so.dummy[2]*time +
iso3[-0.06]*so.dummy[3]*time +
iso4[-0.08]*so.dummy[4]*time /
U(alt2) =
ise1*se.dummy[1]*time +
ise2*se.dummy[2]*time +
ise3*se.dummy[3]*time +
ise4*se.dummy[4]*time +
il1*l.dummy[1]*time +
il2*l.dummy[2]*time +
il3*l.dummy[3]*time +
il4*l.dummy[4]*time +
ia1*a.dummy[1]*time +
ia2*a.dummy[2]*time +
ia3*a.dummy[3]*time +
ia4*a.dummy[4]*time +
ibo1*bo.dummy[1]*time +
ibo2*bo.dummy[2]*time +
ibo3*bo.dummy[3]*time +
ibo4*bo.dummy[4]*time +
ibl1*bl.dummy[1]*time +
ibl2*bl.dummy[2]*time +
ibl3*bl.dummy[3]*time +
ibl4*bl.dummy[4]*time +
ip1*p.dummy[1]*time +
ip2*p.dummy[2]*time +
ip3*p.dummy[3]*time +
ip4*p.dummy[4]*time +
im1*m.dummy[1]*time +
im2*m.dummy[2]*time +
im3*m.dummy[3]*time +
im4*m.dummy[4]*time +
iso1*so.dummy[1]*time +
iso2*so.dummy[2]*time +
iso3*so.dummy[3]*time +
iso4*so.dummy[4]*time
$