# [R] Fractional Factorial Design on 4-level factor

PIKAL Petr petr.pikal at precheza.cz
Tue May 31 11:43:35 CEST 2016

```Hi

I do not consider myself as an expert in factorial design but why do you insist on 4 levels in factors. My opinion is that you need more than 2 levels only if you expect and you want to evaluate nonlinear relationship of the response on such factor.

If you used only 2 levels you could find which factors are influential and they can be further tested on nonlinear response.

And even if you used only 2 levels you have to test 8 factors in at least 16 runs which, with 100 repetitions, gives me 1600 experiments (that seems to me quite a big deal).

Regards
Petr

> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Michael
> Haenlein
> Sent: Tuesday, May 31, 2016 9:05 AM
> To: r-help at r-project.org
> Subject: [R] Fractional Factorial Design on 4-level factor
>
> Dear all,
>
> I am running a simulation experiment with 8 factors that each have 4 levels.
> Each combination is repeated 100 times. If I run a full factorial this would
> mean 100*8^4 = 409,600 runs.
>
> I am trying to reduce the number of scenarios to run using a fractional
> factorial design. I'm interested in estimating the main effects of the 8 factors
> plus their 2-way interactions. Any higher level interactions are not of interest
> to me. My plan is to use a standard OLS regression for that, once the
> simulations are over.
>
> I tried to use the FrF2 package to derive a fractional factorial design but it
> seems that this is only working for factors on two levels. Any idea how I could
> derive a fractional factorial design on factors with four levels?
>
>
> Michael
>
>
>
> Michael Haenlein
> Professor of Marketing
> ESCP Europe
>
>       [[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.

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