dataNested | R Documentation |
This contains a simulated sample of 400 observations which allow establishing 20 clusters with 4 subgroups and 5 subjects in each subgroup, in order to obtain two levels of grouping. This data set is useful to illustrate how to fit a nested model. Two independent gamma frailty parameters with a variance fixed at 0.1 for the cluster effect and at 0.5 for the subcluster effect were generated. Independent survival times were generated from a simple Weibull baseline risk function. The percentage of censoring data was around 30 per cent. The right-censoring variables were generated from a uniform distribution on [1,36] and a left-truncating variable was generated with a uniform distribution on [0,10]. Observations were included only if the survival time is greater than the truncated time.
data(dataNested)
This data frame contains the following columns:
group identification variable
subgroup identification variable
start of interval (0 or truncated time)
end of interval (death or censoring time)
censoring status (0: alive, 1: death)
dichotomous covariate (0,1)
dichotomous covariate (0,1)
V. Rondeau, L. Filleul, P. Joly (2006). Nested frailty models using maximum penalized likelihood estimation. Statistics in Medecine, 25, 4036-4052.
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