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

- Uncontrolled or ‘nuisance’ factors are affecting the results.
- Partial factorial designs are used.

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

Trial | Factor A | Factor B | Factor C |
---|---|---|---|

1 | – | – | + |

2 | + | – | – |

3 | – | + | – |

4 | + | + | + |

In this experiment design, F_{c} = F_{a} * F_{b} (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.

Uday H. says

Excellent and simple explanation about CONFOUNDING

Six Sigma Study Guide says

Thank you! Glad it was helpful.