Hello everybody,
I have a question about designing a discrete choice experiment. My design contains:
Following the book “Marketing Research Methods in SAS” by Warren Kuhfeld, I created the following code:
%mktruns(3 3 3 3 3 4, interact=x1*x6 x2*x6 x3*x6 x4*x6 x5*x6); %mktex(3 3 3 3 3 4, seed = 200, n=144, interact=x1*x6 x2*x6 x3*x6 x4*x6 x5*x6); %macro res; g1 = (x[1,1:5])[+]; * Attributes in alt 1; g2 = (x[2,1:5])[+]; * Attributes in alt 2; bad = bad + (g1 > g2 & x[1,6] < x[2,6]); * Better attributes in 1 and lower price in 1; bad = bad + (g2 > g1 & x[2,6] < x[1,6]); * Better attributes in 2 and lower price in 2; %mend; %mktlab(data=design, int=f1-f2) proc print; run; %choiceff(data=final, model=class(X1-X6), nsets=72, maxiter=20, seed=200, flags=f1-f2, options=relative, restrictions=res, resvars=X1-X6, beta=zero); proc print; by set; id set; run; %mktblock(data=best, nalts=2, nblocks=8, seed=200, maxiter=20);
The final results are as follows:
Finally, I still have the following questions:
Thank you so much!!
Is it correct to use the %mktex macro with n = 144 and the %choiceff macro with nsets = 72? Unfortunately, I don't understand exactly how the recommended size of the kandidate set relates to the size of the choice sets.
Sure. The candidates are simply profiles that might be included in the final design. 144 seems like a great number. Other numbers would work too.
Is my design able to estimate all parameters?
Yes. Your D-efficiency is greater than zero, so yes. There is other output not shown that shows the parameters.
Thank you so much for this quick response, Warren! I run my code again. I assume this is the output you meant in your answer:
I think I still miss something, and three new questions came to my mind:
Thank you so much for your help!
Thank you again for answering my follow-up questions!! Your book really helped me a lot, and I will take a closer look at the chapter again!
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