survivalfragility: Survival Fragility Function

In kippjohnson/fragilityindex: Fragility Index

Description

Compute the fragility of a coefficient in a Cox P-H regression for survival analysis, i.e. the number of removed observations it would take to make a significant-result non-significant. Uses the coxph() function from the survival package.

Usage

survivalfragility(formula, data, covariate = "all.factors.default",
  conf.level = 0.95, verbose = FALSE)

Arguments

formula	Model formula which will be evaluated by coxph()
data	Dataframe with values for model forma, passed to coxph()
covariate	Vector of covariates to find fragility index for. Default is all covariates in formula
conf.level	Significance level
verbose	Logical indicating if function will return verbose results or only fragility index

Value

If verbose is FALSE, returns a list with fragility indices for selected covariates. If verbose is TRUE, returns a list with p-values for each fragility index at each iteration of the algorithm.

Examples

library(survival); data <- lung
data$status = lung$status - 1 # recode status as a 0/1 variable

survivalfragility(Surv(time, status) ~ pat.karno + strata(inst),
                  data, covariate = "pat.karno")

survivalfragility(Surv(time, status) ~ pat.karno + ph.karno + strata(inst),
                  data, verbose = TRUE)
                  #algorithm does not converge for strata(inst)

survivalfragility(Surv(time, status) ~ pat.karno + ph.karno + strata(inst),
                  data, covariate = c("pat.karno","ph.karno"))

kippjohnson/fragilityindex documentation built on May 20, 2019, 10:23 a.m.