Pilot design with attribute level constraints
Posted: Fri Oct 25, 2024 3:48 am
Dear all,
I'm working on an experimental design for my thesis, which aims to understand the substitution of tobacco-related products. For this, I consider a labeled design with an opt-out option. The atributtes and levels are the following:
For the pilot study I am producing a D-efficient design with ngene and the following is the code:
I left the code running for up to two hours, the D-error is 0.941978 and the A-error is 2.78576
Question 1: Since for the alternative cig (i.e. traditional cigarette) there is only one level for the attributes "ext", "hide" and "harm", is the way I have written it in the code correct?
Question 2: This is a design for an experiment. This would be the design I follow for the pilot study. Should I now consider a Bayesian D-efficient design, even though I have no priors? or should I continue with the D-efficient design as presented here?
Question 3: The program returns the following warning: "One or more attributes will not have level balance with the number of rows specified: ecigdisp.price_disp, ecigdisp.externality, ecigrech.price_rech, ecigrech.externality, cig.price_cig, cig.externality". In fact, with two of these attributes we obtain only two levels. What should be the rule for determining the number of rows? I am currently using Rose and Bliemer (2022) equation 3
I am also a bit concerned about the size of the D-error.
Any additional recomendations to improve the design would be really appreciated
Thank you so much
I'm working on an experimental design for my thesis, which aims to understand the substitution of tobacco-related products. For this, I consider a labeled design with an opt-out option. The atributtes and levels are the following:
For the pilot study I am producing a D-efficient design with ngene and the following is the code:
- Code: Select all
; alts= ecigdisp*, ecigrech*, cig*, alt4
; rows= 18
; block= 2
; eff= (mnl,d)
; alg= mfederov
; require:
cig.externality=2, cig.hide=1 , cig.harm=1
;model:
U(ecigdisp) = price[-0.000001]* price_disp[0.025,0.050,0.100,0.160] ? $ Price of disposable cigarette
+ flavour.dummy[0.0001|0.00001]* flavour[0,1,2] ? Flavour: traditional=0, mint=1, fruits=2
+ harm.dummy[-0.0001]* harm[0,1] ? Self-harm: less harmful 0(base), equally harmful=1
+ ext.dummy[-0.001|-0.00001|-0.00001]* externality[0,1,2,3] ? Harm to others: no=0(base), moderate=1, high=2, unkown=3
+ hide.dummy[-0.00001]* hide[0,1] ? Hide smoke: easy to hide=0(base), hard to hide=1
+ int1* price_disp * flavour ? Interaction term between price_disp & flavour
/
U(ecigrech)= price[-0.000001* price_rech[0.035,0.045,0.055,0.080] ? $ Price of rechargable cigarette
+ flavour.dummy[0.0001|0.00001]* flavour ? Flavour: traditional=0, mint=1, fruits=2
+ harm.dummy[-0.0001]* harm ? Self-harm: less harmful than traditional cig=0(base), equally harmful=1
+ ext.dummy[-0.001|-0.00001|-0.00001]* externality ? Harm to others: no harm=0(base), moderate=1, high=2, unkown=3
+ hide.dummy[-0.00001]* hide ? Hide smoke: easy to hide=0(base), hard to hide=1
+ int1* price_rech * flavour ? Interaction term between price_rech & flavour
/
U(cig)= price[-0.000001]* price_cig [0.025,0.05,0.200,0.350] ? $ Price of traditional tocabbo package
+ flavour.dummy[0.0001|0.00001]* flavour ? Flavour: traditional=0, mint=1, fruits=2
+ harm.dummy[-0.0001]* harm ? Self-harm - always harmful (harmful=1)
+ ext[-0.001|-0.00001|-0.00001]* externality ? Harm to others - always harmful
+ hide.dummy[-0.00001]* hide ? Hide smoke - always hard to hide
/
U(alt4)= b0
$
I left the code running for up to two hours, the D-error is 0.941978 and the A-error is 2.78576
Question 1: Since for the alternative cig (i.e. traditional cigarette) there is only one level for the attributes "ext", "hide" and "harm", is the way I have written it in the code correct?
Question 2: This is a design for an experiment. This would be the design I follow for the pilot study. Should I now consider a Bayesian D-efficient design, even though I have no priors? or should I continue with the D-efficient design as presented here?
Question 3: The program returns the following warning: "One or more attributes will not have level balance with the number of rows specified: ecigdisp.price_disp, ecigdisp.externality, ecigrech.price_rech, ecigrech.externality, cig.price_cig, cig.externality". In fact, with two of these attributes we obtain only two levels. What should be the rule for determining the number of rows? I am currently using Rose and Bliemer (2022) equation 3
I am also a bit concerned about the size of the D-error.
Any additional recomendations to improve the design would be really appreciated
Thank you so much