Calculates hazard ratios for a reference vector

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

Usage

# S3 method for class 'coxres'
RelativeRisk(x, df, a_n = c(), ...)

Arguments

x

result object from a regression, class coxres

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

Examples

library(data.table)
df <- data.table::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)
)
formula <- Cox(Starting_Age, Ending_Age, Cancer_Status) ~
  loglinear(a, b, c, 0) + plinear(d, 0) + multiplicative()
res <- CoxRun(formula, df, a_n = list(c(1.1, -0.1, 0.2, 0.5), c(1.6, -0.12, 0.3, 0.4)))
RelativeRisk(res, df)
#> $Risk
#> [1] 1.248731e+46 2.059421e+51 5.258561e+46 9.123755e+50 1.402689e+56
#> [6] 5.354075e+41 3.470271e+51
#>