fit.mult: Fits a multiplicative relative risk model to interval...
In Epi: Statistical Analysis in Epidemiology

Description Usage Arguments Details Value Author(s) References See Also Examples

Utility function.

The model fitted assumes a piecewise constant baseline rate in intervals specified by the argument breaks, and a multiplicative relative risk function.

1 2	fit.mult( y, rates.frame, cov.frame, start )

`y`	Binary vector of outcomes
`rates.frame`	Dataframe expanded from the original data by `expand.data`, cooresponding to covariates for the rate parameters.
`cov.frame`	do., but covariates corresponding to the `formula` argument of `Icens`
`start`	Starting values for the rate parameters. If not supplied, then starting values are generated.

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.

A list with three components:

`rates`	A glm object from a binomial model with log-link, estimating the baseline rates.
`cov`	A glm object from a binomial model with complementary log-log link, estimating the log-rate-ratios
`niter`	Nuber of iterations, a scalar

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

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.

Icens fit.add