From: Chuck Cleland <ccleland_at_optonline.net>

Date: Thu 05 Oct 2006 - 17:18:05 GMT

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Date: Thu 05 Oct 2006 - 17:18:05 GMT

Afshartous, David wrote:

> Hi Harold,

*>
**> Thanks for your response.
**> I'll check out p.224 in P&B, thanks.
**>
**> The null hypothesis is that there is no difference between say
**> A=[time=3, drug=I]
**> and B=[time=3, drug=P], or mu_A = mu_B. If the study is a crossover
**> design, i.e.,
**> each patient receives drug=I and drug=P, I assume that a simple paried
**> t-test could
**> also be employed at time=3.
**>
**> However, I'd like to test this within a mixed effects model; With
**> respect to 3) and 4) below,
**> it seems somewhat difficult to express this specific hypothesis in terms
**>
**> of the model paramaters. Ways in which this null are violated under
**> the mixed effects models could be:
**>
**> 1) there is no interaction between time and Drug, i.e., there is a drug
**> effect but
**> it is the same at all time points. (the specific interaction in 3) below
**> represents
**> the shift of the effect of drug=P from time=1 to time=3 ... so the lack
**> of significance of
**> the paramater "factor(time)3:drugP" doesn't capture what I want)
*

If there is no evidence for an interaction between drug and time, do you still want to ask about the drug effect at time=3, or would you then want to ask about the time-averaged drug effect?

> 2) there is neither interaction nor drug effect (variable Drug not

*> significant).
*

> But both these violations are more general than my null;

*> I think testing fixed effects 3) versus 4) below is what I want, but
**> this
**> also seems strange since possibly the drug effect and drug:time
**> interaction as defined in the model
**> are signicant (with time=1 as the reference baseline).
*

If you fit a model with an intercept, main effects for drug and time, and an interaction, would'nt the coefficient for the drug main effect test the drug effect at a particular time? Perhaps you only need to change the contrasts for time so that time=3 is the reference category?

> Regardless, I assume I would need to employ coef() and vcov() to obtain

*> the needed
**> info ... but I notice that coef() produces 4 values for the intercept of
**> fm1
**> below, does anyone know why this occurs?
*

I think Harold was getting at the fact that you could get an estimate of the drug effect at time=3 simply by setting the contrasts for time in the right way.

> I apologize if my explanation above is confusing, I've tried to make it

*> as clear as possible.
**>
**> thanks again,
**> dave
**>
**>
**>
**> -----Original Message-----
**> From: Doran, Harold [mailto:HDoran@air.org]
**> Sent: Thursday, October 05, 2006 11:40 AM
**> To: Afshartous, David; Spencer Graves
**> Cc: r-help@stat.math.ethz.ch
**> Subject: RE: [R] treatment effect at specific time point within
**> mixedeffects model
**>
**> 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. >>

> ______________________________________________

-- Chuck Cleland, Ph.D. NDRI, Inc. 71 West 23rd Street, 8th floor New York, NY 10010 tel: (212) 845-4495 (Tu, Th) tel: (732) 512-0171 (M, W, F) fax: (917) 438-0894 ______________________________________________ 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 03:24:52 2006

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