Calculates hazard ratios for a reference vector and model

RelativeRisk.coxmodel uses a cox model object and data, to evaluate relative risk in the data using the risk model from the result

Usage

# S3 method for class 'coxmodel'
RelativeRisk(x, df, a_n = NULL, ...)

Arguments

x

cox model object, which could be fed to a regression

df

a data.table containing the columns of interest

a_n

list of initial parameter values, used to determine the number of parameters. May be either a list of vectors or a single vector.

...

extended to match any future parameters needed

Value

returns a class fully describing the model and the regression results

See also

Other Predicted Risk and Rate: RelativeRisk(), RelativeRisk.coxres(), RelativeRisk.formula()

Examples

library(data.table)
df <- data.table(
  UserID = c(112, 114, 213, 214, 115, 116, 117),
  Starting_Age = c(18, 20, 18, 19, 21, 20, 18),
  Ending_Age = c(30, 45, 57, 47, 36, 60, 55),
  Cancer_Status = c(0, 0, 1, 0, 1, 0, 0),
  a = c(0, 1, 1, 0, 1, 0, 1),
  b = c(1, 1.1, 2.1, 2, 0.1, 1, 0.2),
  c = c(10, 11, 10, 11, 12, 9, 11),
  d = c(0, 0, 0, 1, 1, 1, 1),
  e = c(0, 0, 1, 0, 0, 0, 1)
)
control <- list(
  ncores = 1, lr = 0.75, maxiters = c(1, 1),
  halfmax = 1
)
formula <- Cox(Starting_Age, Ending_Age, Cancer_Status) ~
  loglinear(a, b, c, 0) + plinear(d, 0) + multiplicative()
model <- get_form(formula, df)$model
res_risk <- RelativeRisk(model, df, a_n = c(1.1, -0.1, 0.2, 0.5))