If you really want the quadratic terms, you need to keep those variables as
numeric, instead of factors. (You might also want to look into something
like the central composite designs.)
summary() and coef() on the resulting fitted object should give you want you
need. Things like these are covered in the "An Introduction to R" manual...
Andy
From: [EMAIL PROTECTED]
>
> To whom it may concern:
>
> I am trying a factorial design a system of mine that has two factors.
> Each factor was set at four different levels, with one
> replication for each of the combinations. My data is as follows:
>
>
> A B Response
>
> 1 600 2.5 0.0257
>
> 2 600 2.5 0.0254
>
> 3 600 5 0.0217
>
> 4 600 5 0.0204
>
> 5 600 10 0.0191
>
> 6 600 10 0.0210
>
> 7 600 20 0.0133
>
> 8 600 20 0.0139
>
> 9 800 2.5 0.0312
>
> 10 800 2.5 0.0317
>
> 11 800 5 0.0307
>
> 12 800 5 0.0309
>
> 13 800 10 0.0330
>
> 14 800 10 0.0318
>
> 15 800 20 0.0225
>
> 16 800 20 0.0234
>
> 17 1000 2.5 0.0350
>
> 18 1000 2.5 0.0352
>
> 19 1000 5 0.0373
>
> 20 1000 5 0.0361
>
> 21 1000 10 0.0432
>
> 22 1000 10 0.0402
>
> 23 1000 20 0.0297
>
> 24 1000 20 0.0306
>
> 25 1200 2.5 0.0324
>
> 26 1200 2.5 0.0326
>
> 27 1200 5 0.0353
>
> 28 1200 5 0.0353
>
> 29 1200 10 0.0453
>
> 30 1200 10 0.0436
>
> 31 1200 20 0.0348
>
> 32 1200 20 0.0357
>
>
>
> I am able to enter my data into R and obtain an ANOVA table
> (which I have been able to verify as correct using an excel
> spreadsheet), using the following syntax:
>
>
>
> >Factorial<-data.frame(A=c(rep(c("600", "600", "600", "600", "800",
> "800", "800", "800", "1000", "1000", "1000", "1000", "1200",
> "1200", "1200", "1200"), each=2)), B=c(rep(c("2.5", "5",
> "10", "20", "2.5", "5", "10", "20", "2.5", "5", "10", "20",
> "2.5", "5", "10", "20"), each=2)), Response = c(0.0257,
> 0.0254, 0.0217, 0.0204, 0.0191, 0.021, 0.0133, 0.0139,
> 0.0312, 0.0317, 0.0307, 0.0309, 0.033, 0.0318, 0.0225,
> 0.0234, 0.035, 0.0352, 0.0373, 0.0361, 0.0432, 0.0402,
> 0.0297, 0.0306, 0.0324, 0.0326, 0.0353, 0.0353, 0.0453,
> 0.0436, 0.0348, 0.0357))
>
>
>
> > anova(aov(Response~A*B, data=Factorial))
>
>
>
> However, this is as far as I am able to go. I would like to
> obtain the coefficients of my model, but am unable. I would
> also like to use other non-linear models as these factors are
> not linear. Also would like to add A^2 and B^2 into the ANOVA
> and modeling.
>
>
>
> Please can you help with regard and offer some advice. Your
> help is much appreciated.
>
>
>
> Yours sincerely,
>
> Leslie Correia
>
> ------------------------------------------------
>
> Department of Process Engineering
>
> University of Stellenbosch
>
> Private Bag X1
>
> Matieland, 7602
>
> Stellenbosch
>
> Tel: 0837012017
>
> E-mail: [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>
>
> ------------------------------------------------
>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
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and provide commented, minimal, self-contained, reproducible code.
