[R] summary of the effects after logistic regression model

From: andrea evangelista <a.evangelist_at_gmail.com>
Date: Thu 25 Jan 2007 - 15:56:01 GMT


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?

Best regards

Andrea Evangelista
Italy

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