Icens: Fits a regression model to interval censored data.

Description

The models fitted assumes a piecewise constant baseline rate in intervals specified by the argument breaks, and for the covariates either a multiplicative relative risk function (default) or an additive excess risk function.

Usage

Icens( first.well, last.well, first.ill,
         formula, model.type=c("MRR","AER"), breaks,
         boot=FALSE, alpha=0.05, keep.sample=FALSE,
         data )

Arguments

first.well

Time of entry to the study, i.e. the time first seen without event. Numerical vector.

last.well

Time last seen without event. Numerical vector.

first.ill

Time first seen with event. Numerical vector.

formula

Model formula for the log relative risk.

model.type

Which model should be fitted.

breaks

Breakpoints between intervals in which the underlying timescale is assumed constant. Any observation outside the range of breaks is discarded.

boot

Should bootstrap be performed to produce confidence intervals for parameters. If a number is given this will be the number of bootsrap samples. The default is 1000.

alpha

1 minus the confidence level.

keep.sample

Should the bootstrap sample of the parameter values be returned?

data

Data frame in which the times and formula are interpreted.

Value

An object of class "Icens": a list with three components:

rates

A glm object from a binomial model with log-link, estimating the baseline rates, and the excess risk if "AER" is specfied.

cov

A glm object from a binomial model with complementary log-log link, estimating the log-rate-ratios. Only if "MRR" is specfied.

niter

Nuber of iterations, a scalar

boot.ci

If boot=TRUE, a 3-column matrix with estimates and 1-alpha confidence intervals for the parameters in the model.

sample

A matrix of the parameterestimates from the bootstrapping. Rows refer to parameters, columns to bootstrap samples.

Details

The model is fitted by calling either fit.mult or fit.add.

References

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.

Examples

Run this code

# NOT RUN {
data( hivDK )
# Convert the dates to fractional years so that rates are
# expressed in cases per year
for( i in 2:4 ) hivDK[,i] <- cal.yr( hivDK[,i] )

m.RR <- Icens( entry, well, ill,
               model="MRR", formula=~pyr+us, breaks=seq(1980,1990,5),
               data=hivDK)
# Currently the MRR model returns a list with 2 glm objects.
round( ci.lin( m.RR$rates ), 4 )
round( ci.lin( m.RR$cov, Exp=TRUE ), 4 )
# There is actually a print method:
print( m.RR )

m.ER <- Icens( entry, well, ill,
               model="AER", formula=~pyr+us, breaks=seq(1980,1990,5),
               data=hivDK)
# There is actually a print method:
print( m.ER )
  
# }

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