If an orthogonal main effect plan exists for the number of trials you specify, optFederov() in AlgDesign will more than likely find it for you, since such a design should be an optimal design.
Ulrike Grömping wrote: > I think that there is an understandable wish to have the simple orthogonal > plans (and be it only for non-experts to be able to analyse the results > themselves). For mixed levels, there is e.g. the L36 that should be able to > accomodate plans like 2x2x2x3x3x3. Unfortunately, R is not very strong in > this arena. > > If I had more time, I would think about writing a package on comfortably > designing experiments supported e.g. by the catalogues of Chen, J., Sun, > D.X., and Wu, C.F.J. (1993). (A catalogue of two-level and three-level > fractional factorial designs with small runs. International Statistical > Review 61, 131-145.) Such a package should also provide the analysis > facilities for any design generated with it, once it has been enriched with > observed data. (This is a bit different from the typical R spirit, where > users are often required to be experts themselves.) If anyone is planning a > project like this or wants to make a diploma student work on it I would be > interested in contributing. > > For the moment, if you want to implement main effects plans of the orthogonal > sort (e.g. a Taguchi-plan like the L36) you have to use books or tables > published on the internet, if you don't want to use expensive software like > SPSS - not very comfortable, but possible. For example, you can find the L36 - > which would be able to accomodate your 2x2x2x3x3x3 - in > http://www.itl.nist.gov/div898/handbook/pri/section3/pri33a.htm. > > With kind regards, > Ulrike > > >>In general, a "main effects design" need not be orthogonal -- the main >>effects merely need to be estimable. The trick is to estimate them with good >>efficiency, etc. I think you need to consult a local statistician for help >>to understand what these statistical concepts mean. >> >>In your example you could cross the 2^(3-1) with the 3^(3-1) to produce an >>orthogonal design to estimate main effects. But of course that's 72 runs, >>which I don't think you would consider "small." As a previous poster >>commented, there are orthogonal mixed level arrays ("Addleman", "Kempthorne" >>"Youden" -designs are a couple of phrases to try googling on) which stem > >>from the 1960's. I doubt that, in general, they would satisfy your needs. > >>I have not used the AlgDesign package myself. I suggest you direct questions >>about it to the author/maintainer, Bob Wheeler. >> >>-- Bert Gunter >>Genentech Non-Clinical Statistics >>South San Francisco, CA >> >>"The business of the statistician is to catalyze the scientific learning >>process." - George E. P. Box >> > > >>-----Original Message----- >>From: r-help-bounces at stat.math.ethz.ch >>[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of >>statistical.model at googlemail.com >>Sent: Monday, January 23, 2006 12:20 PM >>To: Berton Gunter; statistical.model at googlemail.com; >>r-help at stat.math.ethz.ch >>Subject: [R] R: fractional factorial design in R >> >> >>>Yes, you're right. For, say, a 3 x 5 design, one can do >> >>this in as few as >>7 >>runs -- but only in general by some version of >>one-factor-at-a-time (OFAT) >>designs, which are inefficient. It is easy, via, say >>model.matrix() to >>write a general function to produce these. But I think it's a >>bad idea; more >>efiicient algorithmic designs are better, IMO, which is why I >>suggested >>AlgDesign. You and others are free to disagree, of course. >> >>Hi Bert, >>thanks for your suggestion. >>However, let us say that i need a 2x2x2x3x3x3 design, which >>should not be >>too hard. >>I've loaded AlgDesign, and i am aware now that gen.factorial >>allows me to >>create a full desing. But how to create a main-effects-only >>factorial design >>(orthogonal)? >>I am still not able to produce what i need. The function >>model.matrix.formula is not very clear... :( >> >>Could you please indicate which syntax should i use? I'd >>really appreciate >>your help. >> >>Thanks in advance, >> >>Roberto Furlan >>University of Turin, Italy >> >> >>---------------------------------------- >>La mia Cartella di Posta in Arrivo è protetta con SPAMfighter >>188 messaggi contenenti spam sono stati bloccati con successo. >>Scarica gratuitamente SPAMfighter! >> >> > > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > -- Bob Wheeler --- http://www.bobwheeler.com/ ECHIP, Inc. --- Randomness comes in bunches. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
