interactionRCS (version 0.1.1)

loglinHR: 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",
  ...
)

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

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 boot.ci. Default percentile

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

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")