Cox proprotional hazards univariable models: finalfit model wrapper

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

coxphuni(.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 list of univariable coxph fitted model outputs. Output is of class coxphlist.

Details

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

See also

fit2df, finalfit_merge

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

Examples

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

explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "Surv(time, status)"
colon_s %>%
  coxphuni(dependent, explanatory) %>%
  fit2df()
#>             explanatory                        HR
#> 1 age.factor40-59 years 0.76 (0.53-1.09, p=0.132)
#> 2   age.factor60+ years 0.93 (0.66-1.31, p=0.668)
#> 3        sex.factorMale 1.01 (0.84-1.22, p=0.888)
#> 4    obstruct.factorYes 1.29 (1.03-1.62, p=0.028)
#> 5      perfor.factorYes 1.17 (0.70-1.95, p=0.556)