Dear Robert,

    It is certainly possible to proceed this way. The general topic is "fractional factorial designs"; such designs are often built out of combinations of latin squares or graeco-latin squares. What is the price of this design? The worst issue is that you must assume that there are no interactions between the experimental factors or between the biasing factors and experimental factors. Included in this is that most research in the social sciences does not have adequate power. So think carefully what you might accomplish with 10 people per cell!

   Building a randomization table is pretty easy. A simple algorithm is to build a table with the full representation you are planning (all 12 conditions) then a random vector. Sort on the random vector and you have random assignment.

   Better systems use adaptive assignment to conditions - this will help you best distribute people to "control" the biasing factors.

Good luck.

 Dear Bruce,

Many thanks for your most helpful reply. I am aware of statistical power being a big issue here and think that I might have to restrict myself to testing fewer experimental conditions (although we expect between-condition differences to be fairly large). That being said, I am still curious how the adaptive assignment to conditions you mentioned would work, so I'll try to read up on the topic.

Thanks again, Robert