Crossed and nested factors

Factors are predictor (independent) variables which have been chosen to systematically vary during an experiment to determine their effect on the response (dependent) variable. For example, you want to evaluate the surface finish of metal parts coming from several machines and measured by several operators. Both 'Machine' and 'Operators' are factors in this experiment. 'Machine' and 'Operators' can be crossed or nested factors, depending on how experimenters collect the data.

Crossed

Nested

Two factors are crossed when each level of one factor occurs in combination with each level of the other factor.

Two factors are nested when the levels of one factor are similar but not identical, and each occurs in combination with different levels of another factor.

For example, if you use crossed factors in your experiment, the same three operators would evaluate surface finish from both machines.

For example, if Machine 1 is in Galveston and Machine 2 is in Baton Rouge, each machine will have different operators.

The actual experimental conditions dictate whether you use crossed or nested factors.