Hello,
I am a student and doing choice experiment for the first time. This forum has been very helpful. I have a few questions about Bayesian design. Please excuse me if my questions have been asked before.
My experimental design is unlabeled, characterized by two product alternatives and a no-buy alternative. I am planning to use a Bayesian design. I am about to start the pilot study to define the priors and for this phase I am using a D-efficient design. Below is the script of my D-efficient design:
design
;alts = Alt1*, Alt2*, Alt3
;rows = 16
;eff = (mnl,d)
;block = 2
;model:
U(Alt1) = b1.dummy[0.00001|0.00001]*lc[2,1,0]
+ b2.dummy[0.00001|0.00001|0.00001]*hs[3,2,1,0]
+ b3.dummy[0.00001]*or[1,0]
+ b4[-0.00001]*price[7.99,9.99,10.99,12.99,16.99]/
U(Alt2) = b1.dummy*lc
+ b2.dummy*hs
+ b3.dummy*or
+ b4*price
$
As far as I understand, eight is the minimum number of choice tasks I can use to have my parameters significant at 95% of confidence level (I am planning to use a mixed logit model in my final analysis).
I am planning to use a D-efficient design with 16 choice tasks divided in two blocks of eight choice tasks since this is the D-efficient design I can obtain with the smallest D-error (0.24) while controlling for alternatives dominance and repetitions.
In my study, I will have a relatively small sample (I have different treatments and I can not afford more than 150 observations per each treatment) and I am afraid that blocking the design may request to have a bigger sample. If this is the case, my question is how important is the "size" of the D-error in pilot study phase. Can I use a design with a lower number of choice tasks (eight or twelve) but with a higher D-error (0.54 or 0.34) or is it better to use the 16 choice tasks in two blocks design with a smaller D-error (0.24)?
If the latter option is what you suggest, may I then use a design with 8 choice tasks (one block) in the final Bayesian design?
Thank you very much!