> On Mar 5, 2018, at 2:27 PM, Bert Gunter <bgunter.4...@gmail.com> wrote:
>
> David:
>
> I believe your response on SO is incorrect. This is a standard OFAT (one
> factor at a time) design, so that assuming additivity (no interactions), the
> effects of drugA and drugB can be determined via the model you rejected:
>> three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B,
>> omitting the fourth group of no drugA/yes drugB.
>
> For example, if baseline control (no drugs) has a response of 0, drugA has an
> effect of 1, drugB has an effect of 2, and the effects are additive, with no
> noise we would have:
>
> > d <- data.frame(drugA = c("n","y","y"),drugB = c("n","n","y"))
d2 <- data.frame(trt = c("Baseline","DrugA_only","DrugA_drugB")
>
> > y <- c(0,1,3)
>
> And a straighforward inear model recovers the effects:
>
> > lm(y ~ drugA + drugB, data=d)
>
> Call:
> lm(formula = y ~ drugA + drugB, data = d)
>
> Coefficients:
> (Intercept) drugAy drugBy
> 1.282e-16 1.000e+00 2.000e+00
I think the labeling above is rather to mislead since what is labeled drugB is
actually A&B. I think the method I suggest is more likely to be interpreted
correctly:
> d2 <- data.frame(trt = c("Baseline","DrugA_only","DrugA_drugB"))
> y <- c(0,1,3)
> lm(y ~ trt, data=d2)
Call:
lm(formula = y ~ trt, data = d2)
Coefficients:
(Intercept) trtDrugA_drugB trtDrugA_only
2.564e-16 3.000e+00 1.000e+00
--
David.
>
> As usual, OFAT designs are blind to interactions, so that if they really
> exist, the interpretation as additive effects is incorrect.
>
> Cheers,
> Bert
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
> On Mon, Mar 5, 2018 at 2:03 PM, David Winsemius <dwinsem...@comcast.net>
> wrote:
>
> > On Mar 5, 2018, at 8:52 AM, Ding, Yuan Chun <ycd...@coh.org> wrote:
> >
> > Hi Bert,
> >
> > I am very sorry to bother you again.
> >
> > For the following question, as you suggested, I posted it in both Biostars
> > website and stackexchange website, so far no reply.
> >
> > I really hope that you can do me a great favor to share your points about
> > how to explain the coefficients for drug A and drug B if run anova model
> > (response variable = drug A + drug B). is it different from running three
> > separate T tests?
> >
> > Thank you so much!!
> >
> > Ding
> >
> > I need to analyze data generated from a partial two-by-two factorial
> > design: two levels for drug A (yes, no), two levels for drug B (yes, no);
> > however, data points are available only for three groups, no drugA/no
> > drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group
> > of no drugA/yes drugB. I think we can not investigate interaction between
> > drug A and drug B, can I still run model using R as usual: response
> > variable = drug A + drug B? any suggestion is appreciated.
>
> Replied on CrossValidated where this would be on-topic.
>
> --
> David,
>
> >
> >
> > From: Bert Gunter [mailto:bgunter.4...@gmail.com]
> > Sent: Friday, March 02, 2018 12:32 PM
> > To: Ding, Yuan Chun
> > Cc: r-help@r-project.org
> > Subject: Re: [R] data analysis for partial two-by-two factorial design
> >
> > ________________________________
> > [Attention: This email came from an external source. Do not open
> > attachments or click on links from unknown senders or unexpected emails.]
> > ________________________________
> >
> > This list provides help on R programming (see the posting guide linked
> > below for details on what is/is not considered on topic), and generally
> > avoids discussion of purely statistical issues, which is what your query
> > appears to be. The simple answer is yes, you can fit the model as
> > described, but you clearly need the off topic discussion as to what it
> > does or does not mean. For that, you might try the
> > stats.stackexchange.com<http://stats.stackexchange.com> statistical site.
> >
> > Cheers,
> > Bert
> >
> >
> > Bert Gunter
> >
> > "The trouble with having an open mind is that people keep coming along and
> > sticking things into it."
> > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
> >
> > On Fri, Mar 2, 2018 at 10:34 AM, Ding, Yuan Chun
> > <ycd...@coh.org<mailto:ycd...@coh.org>> wrote:
> > Dear R users,
> >
> > I need to analyze data generated from a partial two-by-two factorial
> > design: two levels for drug A (yes, no), two levels for drug B (yes, no);
> > however, data points are available only for three groups, no drugA/no
> > drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group
> > of no drugA/yes drugB. I think we can not investigate interaction between
> > drug A and drug B, can I still run model using R as usual: response
> > variable = drug A + drug B? any suggestion is appreciated.
> >
> > Thank you very much!
> >
> > Yuan Chun Ding
> >
> >
> > ---------------------------------------------------------------------
> > -SECURITY/CONFIDENTIALITY WARNING-
> > This message (and any attachments) are intended solely f...{{dropped:28}}
> >
> > ______________________________________________
> > R-help@r-project.org<mailto:R-help@r-project.org> mailing list -- To
> > UNSUBSCRIBE and more, see
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> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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.
>
> David Winsemius
> Alameda, CA, USA
>
> 'Any technology distinguishable from magic is insufficiently advanced.'
> -Gehm's Corollary to Clarke's Third Law
>
>
>
>
>
>
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
______________________________________________
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