Confounding in Design of Experiments
Confounding in Design of Experiments. Photo by Boston Public Library

Confounding occurs when you can’t distinguish the effects of certain factor interactions because of other potential factor effects. This most commonly happens when:

For example, let’s look at a simple partial factorial design with confounding:

TrialFactor AFactor BFactor C
1+
2+
3+
4+++

In this experiment design, Fc = Fa * Fb (see Partial/Fractional Factorial Design if you need to revisit the notation used). That means that the effects of factor C on the experiment can’t be distinguished from the interactions between factor A and factor B.

Blocking can help limit confounding by distributing extra factors evenly across all experimental factors.

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