Hello,
In a study exploring transgenerational transmission of anxiety
disorder we investigate whether infants react to experimentally
induced mood changes of their mothers. We measured the time that an
infant needed to cross a cliff (=crossing time) depending on whether
his mother had previously undergone a mood induction (treatment) or
not (control). The treatment is thus a within-subjects factor with two
levels. The outcome, crossing time, is censored as some infants did
not cross the cliff within the predefined time span of 180 seconds.
My first question is which kind of proportional hazard model would be
suitable here. Based on what Ive found in the literature 1) a
marginal model or 2) a frailty (mixed-effects) model would be suitable
here.
If ct=crossing time, event=crossed/not crossed, tr=treatment,
ptid=person ID, then the two models could be implemented like this:
1) coxp(surv(ct,event)~treat+cluster(code)
2) coxme(surv(ct,event)~treat+(1|code)), assuming a random intercept
for each mother/infant
Am I on the right track here?
A second question relates to mediator analyses. We have variables
regarding mothers negative affectivity which, according to our model,
are caused by mood induction and at the same time affect infants
crossing time. I dont know of any mediator model that directly tests
censored outcomes in a repeated measures setting given one (or
several) mediator variable(s).
Any help to either question is greatly appreciated.
Andrea
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