[R-sig-ME] partially crossed design, longitudinal

Cristiano Alessandro cri@@le@@@ndro @ending from gm@il@com
Tue Jun 5 23:32:35 CEST 2018

Hi Thierry,

thanks for your help. While I understand the need of considering the
analysis at the design stage of an experiment, I thought this was a pretty
standard design. Like when testing for a drug, I have a baseline (before
treatment), then I measure at different time point during administration of
the drug (to see the time course of the treatment), and then at different
time point after interruption of the drug administration (to see
retaining). I would be interested to see if the drug is effective, and if
there is a 'time' effect during drug administration and interruption.

Do you have suggestions on how to design this kind of study better for the
future? Thanks!


Do you have suggestions on how to design this study better for the future?

On Tue, May 29, 2018 at 5:18 AM, Thierry Onkelinx <thierry.onkelinx using inbo.be>

> Dear Christiano,
> IMHO, the easiest solution would be to fit the model with the 5 level time
> variable and then calculate the relevant post-hoc contrasts. e.g pert =
> (pert early + pert late) / 2
> Thinking about the analysis at the design stage of an experiment is
> valuable.
> Best regards,
> ir. Thierry Onkelinx
> Statisticus / Statistician
> Vlaamse Overheid / Government of Flanders
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be
> Havenlaan 88
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> 1000 Brussel
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> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
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> 2018-05-25 22:49 GMT+02:00 Cristiano Alessandro <cri.alessandro using gmail.com>
> :
>> Hi all,
>> I have a longitudinal study in which I measure the outcome variables at
>> baseline condition (bas), then I apply a perturbation (pert) and I measure
>> the outcome variable twice (early and late after perturbation is applied),
>> and then I remove the perturbation (noPert) and I measure twice (early and
>> late after perturbation is applied).
>> I would like to use mixed models for this design, but I am a bit confused
>> on how to do it. I could just have a single fixed effects 'time' with
>> levels 1 to 5, where level 1 would be baseline, level 2 would be
>> pert/early
>> and so on. I think this is not the best design though. Alternatively, I
>> could use a fixed effects 'condition' with levels bas, pert, noPert,
>> crossed with another fixed effect 'time' with levels early/late. However,
>> this last design has the problem that I do not have early/late for
>> baseline
>> actually.
>> Do you have suggestion of what to do in a case like this?
>> Thanks a lot
>> Cristiano
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