Description Usage Arguments Value Examples
Compute the fragility of a coefficient in a survival test, 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.
1 2 | survivalfragility(formula, data, covariate = "all.factors.default",
conf.level = 0.95, verbose = FALSE)
|
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 |
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.
1 2 3 4 5 6 7 8 9 10 11 12 | 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"))
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