loglinHR {interactionRCS} | R Documentation |
Linear interaction HR
Description
Generate HR values for a 1 unit increase in a variable at specified points of another interacting variable in a simple Cox interaction model
Usage
loglinHR(
var2values,
model,
data,
var1,
var2,
ci = TRUE,
conf = 0.95,
ci.method = "delta",
ci.boot.method = "perc",
R = 100,
parallel = "multicore",
...
)
Arguments
var2values |
numeric vector of var2 points to estimate |
model |
model of class coxph or cph. If data is NULL, the function expects to find the data in model$x |
data |
data used in the model. If absent, it will attempt to recover the data from the model object. Only used for bootstrap CI |
var1 |
variable that increases by 1 unit from 0 |
var2 |
variable to spline. var2values belong to var2 |
ci |
calculate 95% CI? |
conf |
confidence level. Default 0.95 |
ci.method |
confidence interval method. "delta" performs delta method. "bootstrap" performs bootstrapped CI (slower) |
ci.boot.method |
one of the available bootstrap CI methods from |
R |
number of bootstrap samples if ci.method = "bootstrap". Default 100 |
parallel |
can take values "no", "multicore", "snow" if ci.method = "bootstrap". Default multicore |
... |
other parameters for boot |
Value
if ci = FALSE, a vector of estimate of length(var2values), if ci = TRUE a dataframe with 5 columns, initial values, HR, lower CI, upper CI and SE
Examples
library(survival)
data(cancer)
myformula <- Surv(time, status) ~ ph.karno + ph.ecog + age*sex
model <- coxph(myformula , data = lung )
loglinHR( var2values = 40:80
, model = model , data = lung , var1 ="sex", var2="age"
, ci=TRUE , conf = 0.95 , ci.method = "delta")