Hello,

I am working on a discrete choice experiment for my MSc studies and plan to use explicit or implicit partial profiles. My experiment involves 20 attributes, half of which are binary and the other half discrete valued.

In the manual section related to explicit partial profiles, it is mentioned that all combinations should be created externally, and a randomly selected subset should be fed into the software. For example, in the manual, 1,000 out of 13,608 combinations were randomly selected and provided to the software (p. 189/259).

Given the larger number of attributes and levels in my study, I estimate that there will be approximately 200,000 combinations. I have two main questions:

1- About Determining the Number of Randomly Selected Combinations: Based on my larger set of attributes, how should I determine the appropriate number of randomly chosen combinations to use?

2- About the Efficiency of Reduced Combinations: If I reduce the number of combinations to around 10,000; that is if I randomly choose 10,000 out of 200,000, will NGene still be able to provide an efficient design? Additionally, how is this "efficiency" measured?

I would greatly appreciate any guidance on these questions, as I am working under a tight deadline for my MSc studies.

Thank you very much in advance!