Hi R HELP, I consider the 2^3 factorial experiment described at page 177 of the book Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter (BHH2).
This example use the following data in file BHH2-Data/tab0502.dat at ftp://ftp.wiley.com/ in /sci_tech_med/statistics_experimenters/BHH2-Data.zip run T C K y 1 1 -1 -1 -1 60 2 2 1 -1 -1 72 3 3 -1 1 -1 54 4 4 1 1 -1 68 5 5 -1 -1 1 52 6 6 1 -1 1 83 7 7 -1 1 1 45 8 8 1 1 1 80 Using these data and the R BHH2 package, I was not able to reproduce the very simple results in the BHH2 book. In particular, the following solution will have no meaning since K is categorical: ( plan <- lm(y ~ (T+C+K)^2, data = DATA) ) MEPlot(plan) # Main Effects IAPlot(plan) # Interactions Effects DanielPlot(plan) cubePlot(plan, "T", "C", "K") I decided to rebuilt the data using: plan <- FrF2(8, 3, factor.names=c("T","C","K"), default.level=c("-","+"), randomize = FALSE) ( plan <- add.response(plan, y) ) giving: T C K y 1 - - - 60 2 + - - 72 3 - + - 54 4 + + - 68 5 - - + 52 6 + - + 83 7 - + + 45 8 + + + 80 class=design, type= full factorial Unfortunately the following plot commands do not work: MEPlot(plan) IAPlot(plan) DanielPlot(plan) The error is: Error in MEPlot.design(plan) : The design obj must be of a type containing FrF2 or pb. Why? If I add a fake factor to the plan the plot commands work, but the solution will have no meaning: plan <- FrF2(8, 4, factor.names=c("T","C","K","Q"), default.level=c("-","+"), randomize = FALSE) ( plan <- add.response(plan, y) ) MEPlot(plan) IAPlot(plan) DanielPlot(plan) Sincerely, Andrea B. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org 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.
