Adjusting confidence intervals for paired t-tests of multiple endpoints
Thanks, this comes close to what I need, but the problem is that I have repeated measures in each comparison and SimComp does not seem to handle this. In my experiments, each subject received both placebo and the drug in a randomized order. So, I want to do multiple paired t-test corrected for multiple comparisons. I'm primarily interested in the corrected confidence intervals because I want to plot the mean differences with it. Regards, Erich -----Urspr?ngliche Nachricht----- Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im Auftrag von Mark Difford Gesendet: Montag, 2. M?rz 2009 08:34 An: r-help at r-project.org Betreff: Re: [R] Adjusting confidence intervals for pairedt-tests of multiple endpoints Hi Erich, Look at the SimComp package, which handles multiple endpoints, i.e. columns of response variables. Ratio-comparisons are also handled. Good ready-made range of comparisons; you can also set up your own. Regards, Mark.
Erich Studerus wrote:
Johannes Huesing <johannes at huesing.name> wrote:
Couldn't you re-phrase your model by including timepoint as a continuous regressor and scale as a factor?
Well, the measuring time points are 70 170, 300 and 1440 minutes after drug intake. Since the influence of time is cerainly not linear, I think it's better to treat it as categorical factor. In fact, I already calculated mixed effects models with the four-level factor time and the two-level factor treatment and random effects factors subjects (nested in studies) and studies for each scale. I used mixed effects models, because I'm doing a meta-analysis on the raw data of 8 studies. Thus my dataset has not only a
grouping structure, but is also unbalanced (not all studies did 4 measurements). I'm not sure, if I could extend my model by including another factor for scale, since these scales measure quite different things. I guess, It would be also very difficult the set up appropriate contrasts to
compare each scale on each measuring time point.
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