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: lcorreia@sun.ac.za <mailto:lcorreia@sun.ac.za>
------------------------------------------------
[[alternative HTML version deleted]]
On 8/18/06, Correia, L, Mr <lcorreia at sun.ac.za> <lcorreia at sun.ac.za> wrote:> 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.Try: model <- lm(Response~A*B, data=Factorial) anova(model) Paul
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: lcorreia at sun.ac.za> > 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: lcorreia at sun.ac.za <mailto:lcorreia at sun.ac.za> > > ------------------------------------------------ > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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. > >