[R] summary of the effects after logistic regression model

[Frank E Harrell Jr]

andrea evangelista wrote:
> Dear all, my aim is to estimate the efficacy over time  of a treatment for
> headache prevention.  Data consist of long sequences of repeated binary
> outcomes   (1 if the subject has at least 1 episode of headache  , 0
> otherwise) on subjects randomized to placebo or treatment.
> 
> I have fit a logistic regression model with Huber-White cluster sandwich
> covariance estimator.
> I have put in the model  the variables treatment (trt),sex,age and a
> restricted cubic spline of time (days)  to allow for non-linear treatment
> effects.
> 
> I use the functions lrm and robcov from R Design library:
> 
> h<-lrm(head ~ trt*rcs(days)+ age+ sex,x=T,y=T)
> h.rob<-robcov(h,id)
> 
> I want to estimate treatment effect over time, then:
> 
> k<-contrast(h.rob,list(day=1:240, trt=1),
>                           list(day=1:240, trt=0))
> 
> xYplot(Cbind(exp(Contrast), exp(Lower),exp( Upper)) ~ day, data=k)   #Plot
> of treatment effects (odds ratio).
> 
> The treatment group has a disavantage at the baseline ( for day=1 ,OR=1.16),
> however at day=210 I can see a reduction of headache risk (OR=0.58) on
> treatment group.
> 
> How can I set to 1  the OR of treatment at the baseline (day=1) with R? In
> case, is it corrent?

I don't know of an extremely simple way to do it.  But the baseline may 
be noisy and I'm not sure I would recommend doing what you want.

Frank Harrell

> 
> Best regards
> 
> Andrea Evangelista
> Italy
> 
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