Dear Sir,

I Know that intoducing conditions in the design will not attempt the balanced out-put but I have to putt some restrictions in order to avoid the unfeasible cards. But at the same time, by introducing conditions, we favor correlations between attributes.

In some cards and according to the restrictions related to the price, I found in some cases, Price (F=0) with just an amelioration in one level. In another term, I wonder if these conditions already violate the intent of this design.

Let me explain :

0 Is fixed as the level of status quo (low level).

I have these attributes :

A = water quality / Low – medium – high / (0,1,2)

B = Biodiversity / low medium high / (0,1,2)

C = Recreational facilities / low medium high / (0,1,2)

D = Gas emissions / low medium high / (0,1,2)

E = Health Safety (%) / 0, 25, 50

F = Price (TD) / 0 30 60 90 120 150

I introduced Near-zero priors in order to prepare a bayesian efficient design.

design

alts = alt1*, alt2*, none*

;rows = 12

;block = 2

;eff = (mnl,d)

;con

;cond:

if(alt1.A + alt1.B + alt1.D + alt1.C = 1, alt1.F =0),

if(alt2.A + alt2.B + alt2.D + alt2.C = 1, alt2.F =0),

if(alt1.F =0, alt1.A + alt1.B + alt1.C + alt1.D = 1),

if(alt2.F =0, alt2.A + alt2.B + alt2.D + alt2.C = 1),

if(alt1.F = 0, alt1.E = 0),

if(alt2.F = 0, alt2.E = 0),

if(alt1.E = 0, alt1.F = 0),

if(alt2.E = 0, alt2.F = 0),

if(alt1.A =0, alt1.B < 2),

if(alt2.A =0, alt2.B < 2),

if(alt1.B =0, alt1.A <2),

if(alt2.B= 0, alt2.A <2),

if(alt1.F >= 60, alt1.A + alt1.B + alt1.D >= 4),

if(alt2.F >= 60, alt2.A + alt2.B + alt2.D >= 4),

if(alt1.F > 90, alt1.E = 50),

if(alt2.F > 90, alt2.E = 50),

if(alt1.E = 50, alt1.F > 90),

if(alt2.E = 50, alt2.F > 90),

if(alt1.A + alt1.B + alt1.D >=6, alt1.F >= 120),

if(alt2.A + alt2.B + alt2.D >=6, alt2.F >= 120),

if(alt1.F >= 120, alt1.A + alt1.B + alt1.C + alt1.D >=6),

if(alt2.F >= 120, alt2.A + alt2.B + alt2.C + alt2.D >=6)

;model :

U(alt1)= b1.effects[0.01|0.02]*A[1,2,0]+b2.effects[0.01|0.02]*B[1,2,0]+b3.effects[0.01|0.02]*C[1,2,0]+b4.effects[0.01|0.02]*D[1,2,0]+b5[0.01]*E[0,25,50]+b6[-0.01]*F[0,30,60,90,120,150]/

U(alt2)= b1.effects[0.01|0.02]*A[1,2,0]+b2.effects[0.01|0.02]*B[1,2,0]+b3.effects[0.01|0.02]*C[1,2,0]+b4.effects[0.01|0.02]*D[1,2,0]+b5[0.01]*E[0,25,50]+b6[-0.01]*F[0,30,60,90,120,150]/

U (none)= asc[(u,-0.70,-0.10)]$

I don't know if I have to remove some conditions in order to let levels vary freely ? I want just to know somehow to find logic choice sets without including all these conditions. I know that conditions have to be included to avoid having dominant/dominated alternatives or unreasonable combinations of attribute levels but at the same time, too much of them will affect the distribution of levels (almost unbalanced).

Thanks in advance,

Greetings,