Cox proprotional hazards multivariable models: finalfit model wrapper

Using finalfit conventions, produces multivariable Cox Proportional Hazard regression models for a set of explanatory variables against a survival object.

coxphmulti(.data, dependent, explanatory, ...)

Arguments

.data

Data frame.

dependent

Character vector of length 1: name of survival object in form Surv(time, status).

explanatory

Character vector of any length: name(s) of explanatory variables.

...

Other arguments to pass to coxph.

Value

A multivariable coxph fitted model output. Output is of class coxph.

Details

Uses coxph with finalfit modelling conventions. Output can be passed to fit2df.

See also

fit2df, finalfit_merge

Other finalfit model wrappers: coxphuni(), crrmulti(), crruni(), glmmixed(), glmmulti_boot(), glmmulti(), glmuni(), lmmixed(), lmmulti(), lmuni(), svyglmmulti(), svyglmuni()

Examples

# Cox Proportional Hazards multivariable analysis.
library(finalfit)
library(dplyr)

explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "Surv(time, status)"
colon_s %>%
  coxphmulti(dependent, explanatory) %>%
  fit2df()
#>             explanatory                        HR
#> 1 age.factor40-59 years 0.79 (0.55-1.13, p=0.196)
#> 2   age.factor60+ years 0.98 (0.69-1.40, p=0.926)
#> 3        sex.factorMale 1.02 (0.85-1.23, p=0.812)
#> 4    obstruct.factorYes 1.30 (1.03-1.64, p=0.026)
#> 5      perfor.factorYes 1.08 (0.64-1.81, p=0.785)