Hi all,
I am having trouble understanding the output in the results viewer under the "The OPTEX Procedure". I would like to know the d-efficiency of my design, but there are design numbers 1 - 10 listed in order of decreasing d-efficiency. Which design number relates to the experimental design just created? Can anyone share a link to maybe a tutorial or help page with a description of how to interpret the page I am looking at (screenshot below).
Thank you!
@sarah123 wrote:
Thank you so much!
My understanding of Example 15.1 is that I should be seeing the "best" design, and that the more times the highest d-efficiency score is in the table, the more confident I should be that that is the the highest possible d-efficiency of available design runs.
I don't think "confident" is a word that applies here. In example 15.1, the first 6 different designs have equal D-optimality (in other words, by that criterion, there is no difference between these designs), while designs 7 through 9 are just slightly worse than the first 6.
And that if I were programming (rather than using the interface) I might be able to view Designs 2 and 7 and compare them with each other. Design 2 is equally as d-efficient as the one I am looking at already, however, it would have different combinations of attributes and levels. And Design 7 would be less d-efficient than either Design 1 and Design 2.
I think that's correct, although I would probably phrase it as "Design 7 would be very slightly less d-efficient than either Design 1 and Design 2."
See the first example in the PROC OPTEX Documentation.
Thank you so much!
My understanding of Example 15.1 is that I should be seeing the "best" design, and that the more times the highest d-efficiency score is in the table, the more confident I should be that that is the the highest possible d-efficiency of available design runs.
And that if I were programming (rather than using the interface) I might be able to view Designs 2 and 7 and compare them with each other. Design 2 is equally as d-efficient as the one I am looking at already, however, it would have different combinations of attributes and levels. And Design 7 would be less d-efficient than either Design 1 and Design 2.
Please let me know if I misunderstood anything.
@sarah123 wrote:
Thank you so much!
My understanding of Example 15.1 is that I should be seeing the "best" design, and that the more times the highest d-efficiency score is in the table, the more confident I should be that that is the the highest possible d-efficiency of available design runs.
I don't think "confident" is a word that applies here. In example 15.1, the first 6 different designs have equal D-optimality (in other words, by that criterion, there is no difference between these designs), while designs 7 through 9 are just slightly worse than the first 6.
And that if I were programming (rather than using the interface) I might be able to view Designs 2 and 7 and compare them with each other. Design 2 is equally as d-efficient as the one I am looking at already, however, it would have different combinations of attributes and levels. And Design 7 would be less d-efficient than either Design 1 and Design 2.
I think that's correct, although I would probably phrase it as "Design 7 would be very slightly less d-efficient than either Design 1 and Design 2."
Great! That helps a lot. Thank you
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.