Hi Rolf,
On Monday 09 June 2008 11:16:57 pm Rolf Turner wrote:
> Your approach tacitly assumes --- as did the poster's question --- that
> the probability of passing an item by one method is *independent* of
> whether it is passed by the other method. Which makes the methods
> effectively independent of the nature of the item being assessed!
So it seems I can't just block my primary factor (QA procedure) by nuisance
one (production line) and run Cochran test to see if effects of primary
factor are identical for both its levels.
> Not much actual quality being assured there!
In fact, I am not interested in quality of QA procedures as much as in how
different the results are (error component).
Thanks,
Ivan
> cheers,
>
> Rolf Turner
>
> On 10/06/2008, at 2:57 PM, Greg Snow wrote:
> > here is one approach:
> >
> > res <- cbind( c(10, 5, 1, 12, 3, 8, 7, 2, 10, 1),
> > c(90,15,79,38,7,92,13,78,40,9) )
> >
> > line <- gl(5,1,length=10, labels=LETTERS[1:5])
> >
> > qa <- gl(2,5)
> >
> > fit <- glm( res ~ line*qa, family=binomial )
> >
> > summary(fit)
> >
> > anova(fit, test='Chisq')
> >
> > The interaction terms measure the difference between the different
> > combinations of QA method and production line, if they are all 0,
> > then that means the effect of QA is the same accross production
> > lines and the qa main effect measures the difference between the 2
> > methods (allowing for differences in the prodoction lines), testing
> > if that equals 0 should answer your question.
> >
> > Hope this helps,
> >
> >
> > ________________________________________
> > From: [EMAIL PROTECTED] [EMAIL PROTECTED]
> > On Behalf Of Ivan Adzhubey [EMAIL PROTECTED]
> > Sent: Monday, June 09, 2008 4:28 PM
> > To: r-help@r-project.org
> > Subject: [R] Comparing two groups of proportions
> >
> > Hi,
> >
> > I have a seemingly common problem but I can't find a proper way to
> > approach
> > it. Let's say we have 5 samples (different size) of IC circuits
> > coming from 5
> > production lines (A, B, C, D, E). We apply two different non-
> > destructive QA
> > procedures to each sample, producing to sets of binary outcomes
> > (passed:
> > no/yes). So, we have two groups of proportions:
> >
> > QA1 QA2
> > no/yes no/yes
> > A 10/90 8/92
> > B 5/15 7/13
> > C 1/79 2/78
> > D 12/38 10/40
> > E 3/7 1/9
> >
> > How would I test if the two QA procedures in question give
> > significantly
> > different results, at the same time controlling for the possible
> > production
> > line contribution? It looks like there are many variants of multiple
> > proportions tests available in R and various extra packages but
> > none seems to
> > exactly fit this very simple problem. I would appreciate any advice.
> >
> > Thanks,
> > Ivan
> >
> > The information transmitted in this electronic communica...
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