chevron (version 0.2.7)

coxt02_main: COXT02 Multi-Variable Cox Regression Model Table.

Description

The COXT02 table follows the same principles as the general Cox model analysis and produces the estimates for each of the covariates included in the model (usually the main effects without interaction terms).

Usage

coxt02_main(
  adam_db,
  arm_var = "ARM",
  time_var = "AVAL",
  event_var = "EVENT",
  covariates = c("SEX", "RACE", "AAGE"),
  strata = NULL,
  lbl_vars = "Effect/Covariate Included in the Model",
  multivar = TRUE,
  ...
)
coxt02

Value

the main function returns an rtables object.

Format

An object of class chevron_t of length 1.

Arguments

adam_db

(list of data.frames) object containing the ADaM datasets

arm_var

(string) the arm variable used for arm splitting.

time_var

(string) the time variable in a Cox proportional hazards regression model.

event_var

(string) the event variable in a Cox proportional hazards regression model.

covariates

(character) will be fitted and the corresponding effect will be estimated.

strata

(character) will be fitted for the stratified analysis.

lbl_vars

(string) text label for the a Cox regression model variables.

multivar

(flag) indicator of whether multivariate cox regression is conducted.

...

Further arguments passed to tern::control_coxreg().

Functions

• coxt02_main(): Main TLG function

Details

• The reference arm will always the first level of arm_var. Please change the level if you want to change the reference arms.

• The table allows confidence level to be adjusted, default is two-sided 95%.

• The stratified analysis is with DISCRETE tie handling (equivalent to tern::control_coxreg(ties = "exact") in R).

• Model includes treatment plus specified covariate(s) as factor(s) or numeric(s), with "SEX", "RACE" and "AAGE" as default candidates.

• The selection of the covariates and whether or not there is a selection process (vs. a fixed, pre-specified list) needs to be pre-specified.

• For pairwise comparisons using the hazard ratio, the value for the control group is the denominator.

• Keep zero-count rows unless overridden with prune_0 = TRUE.

Examples

library(dunlin)

proc_data <- log_filter(syn_data, PARAMCD == "CRSD", "adtte")

run(coxt02, proc_data)

run(coxt02, proc_data, covariates = c("SEX", "AAGE"), strata = c("RACE"), conf_level = 0.90)