From: Doran, Harold <HDoran_at_air.org>

Date: Thu 05 Oct 2006 - 15:39:31 GMT

R-help@stat.math.ethz.ch 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. Received on Fri Oct 06 01:48:14 2006

Date: Thu 05 Oct 2006 - 15:39:31 GMT

Hi David:

In looking at your original post it is a bit difficult to ascertain exactly what your null hypothesis was. That is, you want to assess whether there is a treatment effect at time 3, but compared to what. I think your second post clears this up. You should refer to pages 224- 225 of Pinhiero and Bates for your answer. This shows how to specify contrasts.

> -----Original Message-----

*> From: r-help-bounces@stat.math.ethz.ch
**> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
**> Afshartous, David
**> Sent: Thursday, October 05, 2006 11:08 AM
**> To: Spencer Graves
**> Cc: r-help@stat.math.ethz.ch
**> Subject: Re: [R] treatment effect at specific time point
**> within mixedeffects model
**>
**> Hi Spencer,
**>
**> Thanks for your reply.
**> I don't think this answers my question.
**>
**> If I understand correctly, your model simply removes the
**> intercept and thus the intercept in fm1 is the same as the
**> first time factor in fm1a ... but am I confused as to why the
**> other coefficient estimates are now different for the time
**> factor if this is just a re-naming.
**> The coefficient estimates for the interactions are the same
**> for fm1 and fm1a, as expected.
**>
**> But my question relates to the signifcance of drug at a
**> specific time point, e.g., time = 3. The coeffecieint for
**> say "factor(time)3:drugP" measures the interaction of the
**> effect of drug=P and time=3, which is not testing what I want
**> to test. Based on the info below, I want to compare 3) versus 4).
**>
**> 1) time=1, Drug=I : Intercept
**> 2) time=1, Drug=P : Intercept + DrugP
**> 3) time=3, Drug=I : Intercept + factor(time)3
**> 4) time=3, Drug=P : Intercept + factor(time)3 + DrugP +
**> factor(time)3:drugP
**>
**> I'm surprised this isn't simple or maybe I'm missing
**> something competely.
**>
**> thanks
**> dave
**>
**>
**>
**>
**>
**> -----Original Message-----
**> From: Spencer Graves [mailto:spencer.graves@pdf.com]
**> Sent: Wednesday, October 04, 2006 7:11 PM
**> To: Afshartous, David
**> Cc: r-help@stat.math.ethz.ch
**> Subject: Re: [R] treatment effect at specific time point
**> within mixed effects model
**>
**> Consider the following modification of your example:
**>
**> fm1a = lme(z ~ (factor(Time)-1)*drug, data = data.grp, random
**> = list(Patient = ~ 1) )
**>
**> summary(fm1a)
**> <snip>
**> Value Std.Error DF t-value p-value
**> factor(Time)1 -0.6238472 0.7170161 10 -0.8700602 0.4047
**> factor(Time)2 -1.0155283 0.7170161 10 -1.4163256 0.1871
**> factor(Time)3 0.1446512 0.7170161 10 0.2017405 0.8442
**> factor(Time)4 0.7751736 0.7170161 10 1.0811105 0.3050
**> factor(Time)5 0.1566588 0.7170161 10 0.2184871 0.8314
**> factor(Time)6 0.0616839 0.7170161 10 0.0860286 0.9331
**> drugP 1.2781723 1.0140139 3 1.2605077 0.2966
**> factor(Time)2:drugP 0.4034690 1.4340322 10 0.2813528
**> 0.7842 factor(Time)3:drugP -0.6754441 1.4340322 10 -0.4710104
**> 0.6477 factor(Time)4:drugP -1.8149720 1.4340322 10
**> -1.2656424 0.2343 factor(Time)5:drugP -0.6416580 1.4340322
**> 10 -0.4474502 0.6641 factor(Time)6:drugP -2.1396105
**> 1.4340322 10 -1.4920240 0.1666
**>
**> Does this answer your question?
**> Hope this helps.
**> Spencer Graves
**>
**> Afshartous, David wrote:
**> >
**> > All,
**> >
**> > The code below is for a pseudo dataset of repeated measures on
**> > patients where there is also a treatment factor called
**> "drug". Time
**> > is treated as categorical.
**> >
**> > What code is necessary to test for a treatment effect at a
**> single time
**>
**> > point,
**> > e.g., time = 3? Does the answer matter if the design is a
**> crossover
**> > design,
**> > i.e, each patient received drug and placebo?
**> >
**> > Finally, what would be a good response to someone that
**> suggests to do
**> > a simple t-test (paired in crossover case) instead of the
**> test above
**> > within a mixed model?
**> >
**> > thanks!
**> > dave
**> >
**> >
**> >
**> > z = rnorm(24, mean=0, sd=1)
**> > time = rep(1:6, 4)
**> > Patient = rep(1:4, each = 6)
**> > drug = factor(rep(c("I", "P"), each = 6, times = 2)) ## P =
**> placebo, I
**>
**> > = Ibuprofen dat.new = data.frame(time, drug, z, Patient) data.grp =
**> > groupedData(z ~ time | Patient, data = dat.new)
**> > fm1 = lme(z ~ factor(time) + drug + factor(time):drug, data =
**> > data.grp, random = list(Patient = ~ 1) )
**> >
**> > ______________________________________________
**> > R-help@stat.math.ethz.ch 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.
**> >
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch 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.
*

>

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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. Received on Fri Oct 06 01:48:14 2006

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