Fitting Proportional Hazards Models

Function to fit proportional hazards (PH) models.

Usage

phreg(formula, data, baseline = "weibull", dist = NULL, init = 0, ...)

Arguments

formula

an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.

data

data an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which function is called.

baseline

the chosen baseline distribution; options currently available are: exponential, weibull, lognormal, loglogistic and Birnbaum-Saunders (fatigue) distributions.

dist

alternative way to specify the baseline distribution (for compatibility with the survreg function); default is NULL.

init

initial values specification (default value is 0); see the detailed documentation for init in optimizing.

...

further arguments passed to other methods.

Value

phreg returns an object of class "phreg" containing the fitted model.

Examples

# \donttest{
library(survstan)
fit <- phreg(Surv(futime, fustat) ~ ecog.ps + rx, data = ovarian, baseline = "weibull")
summary(fit)
#> Call:
#> phreg(formula = Surv(futime, fustat) ~ ecog.ps + rx, data = ovarian, 
#>     baseline = "weibull")
#> 
#> Proportional hazards model fit with weibull baseline distribution: 
#> 
#> Regression coefficients:
#>         Estimate Std. Error z value Pr(>|z|)
#> ecog.ps  0.43563    0.58727  0.7418   0.4582
#> rx      -0.59811    0.58823 -1.0168   0.3093
#> 
#> Baseline parameters:
#>         Estimate Std. Error       2.5%     97.5%
#> alpha    1.13138    0.28535    0.69012    1.8548
#> gamma  988.99454 1164.58729   98.37037 9943.1386
#> --- 
#> loglik = -97.08449   AIC = 202.169 
# }