Dear collegues,
As PhD student, I want to set up a Discrete Choice Experiment in a consumers survey. The main objective is to measure consumer willingness to pay for multi-labelled seafood products. Following focus group and expert opinion, my attributes and their corresponding levels will be the following :
My full factorial desing is composed by 64 attribute combinations (4*4*4). To generate it, i used the following code
I obtained a table which present the entire combination.
I therefore have to select a fractonnial factorial design for my survey. To do so, i used the following code:
I aim to propose to each individual in my survey to choose between two options and one output option. Each individual will have to do this operation three times.
I don't understand how to select the fractionnal design with the higher Defficenty ... Each time I run the last two lines of my code, the Defficienty score changes. I am confused about the procedure to follow. And I haven't introduced the opt-out yet for the moment in my design ...
Sorry for these questions, I am just starting to get interested in these issues of DCE.
If you want more information to clarify my position, i remain available
Best Regards
Jean-François DEWALS
As PhD student, I want to set up a Discrete Choice Experiment in a consumers survey. The main objective is to measure consumer willingness to pay for multi-labelled seafood products. Following focus group and expert opinion, my attributes and their corresponding levels will be the following :
| Attributes | Level |
| Price | Market price; +10%; + 20%; +30% |
| Labels | None; Ecolabel; Health Allegations; Both labels |
| Production Method | Wild cod; Raised salmon; Wild seabass; raised seabass |
My full factorial desing is composed by 64 attribute combinations (4*4*4). To generate it, i used the following code
Code:
matrix attrib = 4,4,4 genfact, levels (attrib) list, separator (4)
I therefore have to select a fractonnial factorial design for my survey. To do so, i used the following code:
Code:
rename x1 price rename x2 labels rename x3 species recode price (1=0) (2=1) (3=2) (4=3) recode labels (1=0) (2=1) (3=2) (4=3) recode species (1=0) (2=1) (3=2) (4=3) ******* Test de Defficient ******* matrix b = J(1,9,0) dcreate i.price i.labels i.species, nalt(2) nset(12) bmat(b)
I don't understand how to select the fractionnal design with the higher Defficenty ... Each time I run the last two lines of my code, the Defficienty score changes. I am confused about the procedure to follow. And I haven't introduced the opt-out yet for the moment in my design ...
Sorry for these questions, I am just starting to get interested in these issues of DCE.
If you want more information to clarify my position, i remain available
Best Regards
Jean-François DEWALS
