Epi: Icens – R documentation

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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.

Details

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

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.

Author(s)

Martyn Plummer, martyn.plummer@r-project.org, Bendix Carstensen, b@bxc.dk

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

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 )

Epi

Statistical Analysis in Epidemiology

v2.44

GPL-2

Authors

Bendix Carstensen [aut, cre], Martyn Plummer [aut], Esa Laara [ctb], Michael Hills [ctb]

Initial release

2021-02-28