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Fractional factorial aliases and foldover — Examples
1 · Prerequisites
2 · Summary
The first example computes all four alias classes in the fraction with . The second computes the exact residual relations after a complete mirror foldover and a one-factor follow-up. It contrasts resolution IV after the full mirror with a partial design that still aliases one main effect with an interaction.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The alias classes in a fraction
Example
Take with factors and the positive generator equation , conventionally written . The four runs, in order, are , , , and . The complete equal-column alias classes are
In the unrestricted model with all eight factorial terms, each pair contributes through its coefficient sum. Separating a main effect from its aliased interaction therefore requires additional runs or an explicit sparsity or hierarchy assumption.
Facts & Assumptions
Given: , the generator equation , the four runs displayed in the Example, and the unrestricted fixed-design model with columns for all subsets of .
Regular two-level fractions, signed defining relations, and resolution: a regular fraction is specified by independent generator equations; is generated by their signed words, and equal-column aliases are columns that agree on every run.
The defining subgroup gives the exact alias relations: and have equal columns exactly when .
Aliased factorial columns prevent separate coefficient identification: if two distinct columns satisfy , their contribution depends only on , so the coefficients are not separately identifiable in the unrestricted model.
Verification
Choose freely and set . This gives exactly the four runs listed in the Example, one for each of the four choices of , and every run satisfies .
Here . By [F2], effects have equal columns exactly when their symmetric difference is either or . Pairing each subset with its complement gives precisely , , , and ; these four pairs exhaust the eight subsets.
In each listed pair the columns are equal, so [F3] shows that the corresponding terms enter the fitted vector through , , , or , respectively. The design by itself does not identify the two coefficients within any pair separately.
Sources
Oehlert §18.2 and NIST/SEMATECH §§5.3.3.4.1–5.3.3.4.3 give the standard half-fraction and its alias notation. The four-row enumeration and coefficient ambiguity are verified locally.
Full and targeted foldovers of a resolution III fraction
Example
Use factors and the regular fraction generated by
Writing for the identity word, its defining relations are and , so and the initial resolution is III. A complete mirror foldover yields the regular fraction with : each subset remains paired with , so remains aliased with while and separate. Reversing only factor yields the regular fraction with : each remains paired with , so separates from but remains aliased with . The targeted follow-up therefore leaves resolution III and a specific coefficient ambiguity; this is an exact residual alias list, not a claim that all main effects are clear.
Facts & Assumptions
Given: The five factors and generator equations in the Example, the complete mirror foldover , the partial foldover , and the unrestricted fixed-design linear model with all factorial columns on the augmented runs.
Regular two-level fractions, signed defining relations, and resolution: signed words multiply by symmetric difference, and resolution is the shortest nonidentity defining-word length.
The defining subgroup gives the exact alias relations: is generated by the independent signed generators and gives all equal- or opposite-column alias relations.
Full and partial foldovers separate aliases by parity: after reversing factor set , the residual relation subgroup is .
Aliased factorial columns prevent separate coefficient identification: equal columns in an unrestricted fixed-design model contribute only through the sum of their coefficients, and the two coefficients are not separately identifiable.
Verification
The equations give and , so the defining words are and . Their product is because the repeated cancels in symmetric difference. The two incidence vectors are nonzero and distinct; over , two nonzero vectors are dependent only if equal, so these generators are independent. By [F2] these and the identity are exactly the four words in . Their nonidentity lengths are , hence the initial resolution is III.
For the complete mirror, [F3] changes the signs of the length-three relations ABD and CDE but preserves ABCE, giving . The two eight-run blocks are disjoint because ABD has opposite signs on them, and both lie in ; choosing freely determines , so and their union is exactly this regular fraction. Its aliases are precisely with , so remains paired with , while is absent and that pair separates. The shortest residual word has length .
For the partial foldover on , [F3] changes ABD and ABCE but preserves CDE, giving . The two eight-run blocks are disjoint because ABD has opposite signs on them, and both lie in ; choosing freely determines , so their union is all 16 runs in this regular fraction. The complete residual pairs are precisely and : this includes and excludes the original relation . The shortest residual word has length .
The retained columns in the partial design contribute as . By [F4], only this combination enters the fitted vector for this pair, so the partial follow-up does not separately identify and without a restriction or further runs.
Sources
Oehlert §§18.2, 18.4, and 18.7 support the generator, resolution, and full-foldover conventions. NIST/SEMATECH §§5.3.3.8.1–5.3.3.8.2 covers mirror and selected-factor follow-ups. All relation products and residual alias sets in this example are computed explicitly.
Sources
- Gary W. Oehlert, A First Course in Design and Analysis of Experiments, Chapter 18, §18.2
- NIST/SEMATECH e-Handbook of Statistical Methods, §§5.3.3.4.1–5.3.3.4.3
- Gary W. Oehlert, A First Course in Design and Analysis of Experiments, Chapter 18, §§18.2, 18.4, and 18.7
- NIST/SEMATECH e-Handbook of Statistical Methods, §§5.3.3.8.1–5.3.3.8.2