I have a question that is not (yet) related to a specific Sawtooth product, but rather of a general kind:

I want to do a CVA with 10 factors, each having two levels (i.e. 210), and need to estimate not only main effects, but also two- and three-way interactions. As the full factorial design is rather big (1024 profiles), I considered a fractional factorial design to be a good idea. So far, so good (I think).

As a next step, I considered either using an orthogonal array of strength 7 / resolution 8 or create a D-efficient design that fits my requirements. However, I have a problem with both of these options:

A) I found two orthogonal arrays of strength 7 that would be applicable, but they need 128 or 1024 runs, respectively. As this number obviously needs to be “reduced” I was wondering: Would I be able to create a certain number of blocks (out of one of these two arrays) to reduce the number of runs for the individual and then be able to estimate main effects on the individual and the interaction effects on an aggregate level? And if this is the case, how would I do this?

B) As I did not find an answer to the previous question, I wanted to check if I can create a D-efficient (not necessarily optimal) design of resolution 8 with a manageable number of runs for the individual - Warren Kuhfeld suggests using SAS for this task. However, I don’t have access to this software right now. So the questions here are: Do you know if there is any other software with which I could equally create and test the described design? If yes: Which one (SPSS and Stata do not seem to work; R seems to be an option…)? If no: Do you think SAS can really help me with my problem? (In order to better be able to assess if buying this software would be a sensible investment for me…)

In any case, I’m very thankful for any kind of suggestions or recommendations that you might have! Thank you a lot in advance!