WeibullReg {SurvRegCensCov}

Weibull Regression for Survival Data

Description

WeibullReg performs Weibull regression using the survreg function, and transforms the estimates to a more natural parameterization. Additionally, it produces hazard ratios (corresponding to the proportional hazards interpretation), and event time ratios (corresponding to the accelerated failure time interpretation) for all covariates.

Usage

WeibullReg(formula, data = parent.frame(), conf.level = 0.95)

Arguments

formula

A Surv formula.

data

The dataset containing all variables referenced in formula.

conf.level

Specifies that 1 - \alpha level confidence intervals for the hazard and event time ratios should be produced.

Details

Details regarding the transformations of the parameters and their standard errors can be found in Klein and Moeschberger (2003, Chapter 12). An explanation of event time ratios for the accelerated failure time interpretation of the model can be found in Carroll (2003). A general overview can be found in the vignette("weibull") of this package, or in the documentation for ConvertWeibull.

Value

formula

The formula for the Weibull regression model.

coef

The transformed maximum likelihood estimates, with standard errors.

HR

The hazard ratios for each of the predictors, with 1 - \alpha level confidence intervals.

ETR

The event time ratios (acceleration factors) for each of the predictors, with 1 - \alpha level confidence intervals.

summary

The summary output from the original survreg model.

Author(s)

Sarah R. Haile, Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, [e-mail]

References

Carroll, K. (2003). On the use and utility of the Weibull model in the analysis of survival data. Controlled Clinical Trials, 24, 682–701.

Klein, J. and Moeschberger, M. (2003). Survival analysis: techniques for censored and truncated data. 2nd edition, Springer.

See Also

Requires the package survival. This function depends on ConvertWeibull. See also survreg.

Examples

data(larynx)
WR <- WeibullReg(Surv(time, death) ~ factor(stage) + age, data = larynx)
WR