[R-sig-teaching] Analyze Nested and Split-Plot Designs with R

[Richard M. Heiberger]

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 <sstoline at gmail.com> 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 <rmh at temple.edu> 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 <sstoline at gmail.com> 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
>> > sstoline at gmail.com
>> >
>> >         [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > R-sig-teaching at r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
>
>
>
>
> --
> Steven M. Stoline
> 1123 Forest Avenue
> Portland, ME 04112
> sstoline at gmail.com