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Fractional Factorial Experiments and Surveys

I'm reading and greatly enjoyed Statistics for Experimenters. The book emphasizes careful thinking about experimentation in addition to careful explanation of statistical methods.

One of the main topics is the use of fractional factorial designs. In these designs, some of the experimental conditions are confounded with higher order interactions (the latter are assumed to be negligible). These designs can be more efficient when the assumptions are correct. And fitting these designs into a sequence of experiments can make them very powerful.

This has me thinking about how we often conduct experiments on surveys. We often vary a single factor and then report the results with a slim description of the other "essential survey conditions" -- i.e. other factors which are not explored. These other conditions are potential confounders in these experimental designs.

If more of these essential conditions were reported, it might help make sense of experimental results that are sometimes contradictory -- that is, if a confounding design factor can be identified. It may point the way for further experiments that test these potential confounders. In this manner, our knowledge about survey design factors could increase.
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  1. Matt JansMarch 7, 2012 at 7:16 PM

    James, it's been a while since I've seen this phrase! I was helping a professor design a fractional factorial experiment years back so I have some interesting references if you ever need them. Mostly Taguchi Method, which is what he was using.

    I like your general comment about the differences between survey methodology research (and our treatment of essential survey conditions...out "protocol and stimuli" to use lab lingo) and experimental lab research. Having done both the distinction resonates well with me.

    Even in the lab-based social sciences you can find "house effects"...situations where one lab can get a particular experimental effect and another can't, even if it seems like they're doing the same thing.

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