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.

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

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)