Nothing is wrong. The "Warning" makes sure you know that there is no numerator term in the "Within" stratum. Since that is intended by this design, all is well.
Any differences in numerical values are most likely an artifact of rounding. Please be specific about what you typed and what you received when asking questions on this list. In this case, there are three models and three tables in Montgomery. Your question doesn't say which you are asking about, nor what you differences you are seeing. The general comment from the R-help list applies here: PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Rich On Thu, Jan 8, 2015 at 3:04 PM, Steven Stoline <[email protected]> wrote: > Dear Rich: > > First thank you very much. it helped a lot. > > The F value and its p-values corresponding to the factor "Supplier"are > different from the ones in the textbook, Montgomery 8th ed. But conclusion > stay same (Pvalue > 0.05) > > > > In the last model (the third one) used for Table 14.6 , I am not sure what > is wrong. > > >> MontEx14.1.aov3 <- aov(Purity ~ Supplier + Error(Supplier:Batch), >> data=MontEx14.1) > > Warning message: > > In aov(Purity ~ Supplier + Error(Supplier:Batch), data = MontEx14.1) : > Error() model is singular > > > > > many thanks > Steven > > On Thu, Jan 8, 2015 at 1:58 PM, Richard M. Heiberger <[email protected]> wrote: >> >> Steven, >> >> I assume you mean Montgomery 8th edition (he changed chapter numbers >> recently). >> >> Please state what you expect as output. >> >> For your first attempt, you have the case wrong (purity instead of >> Purity). >> >> Are you reading Supplier and Batch as factors. It can't be determined >> from the >> printed table in your email. Use dump (or dput) next time. dput is >> designed for R. >> >> With the above corrections, your first model formula gives Table 14.4 >> and your second >> formula gives Table 14.5. >> >> To get Table 14.6 you need to use the Error() function in the model >> formula. >> Here are statements for all three tables. >> >> Rich >> >> ## dump("MontEx14.1","") >> MontEx14.1 <- >> structure(list(Supplier = structure(c(1L, 1L, 1L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >> 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("1", >> "2", "3"), class = "factor"), Batch = structure(c(1L, 1L, 1L, >> 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, >> 3L, 3L, 4L, 4L, 4L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, >> 4L), .Label = c("1", "2", "3", "4"), class = "factor"), Purity = c(1L, >> -1L, 0L, -2L, -3L, -4L, -2L, 0L, 1L, 1L, 4L, 0L, 1L, -2L, -3L, >> 0L, 4L, 2L, -1L, 0L, -2L, 0L, 3L, 2L, 2L, 4L, 0L, -2L, 0L, 2L, >> 1L, -1L, 2L, 3L, 2L, 1L)), .Names = c("Supplier", "Batch", "Purity" >> ), row.names = c(NA, -36L), class = "data.frame") >> >> >> >> MontEx14.1$Supplier <- factor(MontEx14.1$Supplier) >> MontEx14.1$Batch <- factor(MontEx14.1$Batch) >> >> MontEx14.1.aov1 <- aov(Purity ~ Supplier/Batch, data=MontEx14.1) >> summary(MontEx14.1.aov1) >> >> MontEx14.1.aov2 <- aov(Purity ~ Supplier*Batch, data=MontEx14.1) >> summary(MontEx14.1.aov2) >> >> MontEx14.1.aov3 <- aov(Purity ~ Supplier + Error(Supplier:Batch), >> data=MontEx14.1) >> summary(MontEx14.1.aov3) >> >> >> On Thu, Jan 8, 2015 at 1:06 PM, Steven Stoline <[email protected]> wrote: >> > Dear All: >> > >> > example 14.1, Montgomery, chapter 14. *Supplier* is a *fixed factor*, >> > *Batches* is a *random factor* nested within the fixed factor Supplier. >> > >> > How to analyze these data in R in two ways: >> > >> > 1- Nested Design >> > >> > fit <- aov(purity~Supplier/Batch) >> > >> > >> > it did not give me the expected output. >> > >> > >> > 2- as a factorial (suppliers Fixed, Batches Random) >> > >> > fit.out <- aov(Purity~Supplier*Batch, data=have) >> > >> > it did not give me the expected output. >> > >> > >> > Here is the data set: >> > =============== >> > >> >> data >> > Supplier Batch Purity >> > 1 1 1 >> > 1 1 -1 >> > 1 1 0 >> > 1 2 -2 >> > 1 2 -3 >> > 1 2 -4 >> > 1 3 -2 >> > 1 3 0 >> > 1 3 1 >> > 1 4 1 >> > 1 4 4 >> > 1 4 0 >> > 2 1 1 >> > 2 1 -2 >> > 2 1 -3 >> > 2 2 0 >> > 2 2 4 >> > 2 2 2 >> > 2 3 -1 >> > 2 3 0 >> > 2 3 -2 >> > 2 4 0 >> > 2 4 3 >> > 2 4 2 >> > 3 1 2 >> > 3 1 4 >> > 3 1 0 >> > 3 2 -2 >> > 3 2 0 >> > 3 2 2 >> > 3 3 1 >> > 3 3 -1 >> > 3 3 2 >> > 3 4 3 >> > 3 4 2 >> > 3 4 1 >> > >> > >> > many thanks >> > Steven >> > >> > -- >> > Steven M. Stoline >> > 1123 Forest Avenue >> > Portland, ME 04112 >> > [email protected] >> > >> > [[alternative HTML version deleted]] >> > >> > _______________________________________________ >> > [email protected] mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-sig-teaching > > > > > -- > Steven M. Stoline > 1123 Forest Avenue > Portland, ME 04112 > [email protected] _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
