Utility function.
The model fitted assumes a piecewise constant baseline rate in
intervals specified by the argument breaks
, and a
multiplicative relative risk function.
fit.mult( y, rates.frame, cov.frame, start )
Binary vector of outcomes
Dataframe expanded from the original data by
expand.data
, cooresponding to covariates for the rate
parameters.
do., but covariates corresponding to the
formula
argument of Icens
Starting values for the rate parameters. If not supplied, then starting values are generated.
A list with three components:
A glm object from a binomial model with log-link, estimating the baseline rates.
A glm object from a binomial model with complementary log-log link, estimating the log-rate-ratios
Nuber of iterations, a scalar
The model is fitted by alternating between two generalized linear models where one estimates the underlying rates in the intervals, and the other estimates the log-relative risks.
B Carstensen: Regression models for interval censored survival data: application to HIV infection in Danish homosexual men. Statistics in Medicine, 15(20):2177-2189, 1996.
CP Farrington: Interval censored survival data: a generalized linear modelling approach. Statistics in Medicine, 15(3):283-292, 1996.
# NOT RUN {
data( HIV.dk )
# }
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