COXT01
(Default) Cox Regression Model Table.Cox models are the most commonly used methods to estimate the magnitude of the effect in survival analyses. It assumes proportional hazards; that is, it assumes that the ratio of the hazards of the two groups (e.g. two arms) is constant over time. This ratio is referred to as the "hazard ratio" and is one of the most commonly reported metrics to describe the effect size in survival analysis.
coxt01_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 = FALSE,
...
)coxt01_pre(adam_db, arm_var = "ARM", ...)
coxt01_post(tlg, prune_0 = FALSE, ...)
coxt01
the main function returns an rtables
object
the preprocessing function returns a list
of data.frame
.
the postprocessing function returns an rtables
object or an ElementaryTable
(null report).
An object of class chevron_t
of length 1.
(list
of data.frames
) object containing the ADaM
datasets
(string
) the arm variable used for arm splitting.
(string
) the time variable in a Cox proportional hazards regression model.
(string
) the event variable in a Cox proportional hazards regression model.
(character
) will be fitted and the corresponding effect will be estimated.
(character
) will be fitted for the stratified analysis.
(string
) text label for the a Cox regression model variables.
(flag
) indicator of whether multivariate cox regression is conducted.
Further arguments passed to tern::control_coxreg()
.
(TableTree
, Listing
or ggplot
) object typically produced by a main
function.
(flag
) remove 0 count rows
coxt01_main()
: Main TLG function
coxt01_pre()
: Preprocessing
coxt01_post()
: Postprocessing
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
.
library(dunlin)
proc_data <- log_filter(syn_data, PARAMCD == "CRSD", "adtte")
proc_data <- log_filter(proc_data, ARMCD != "ARM C", "adsl")
run(coxt01, proc_data)
run(coxt01, proc_data, covariates = c("SEX", "AAGE"), strata = c("RACE"), conf_level = 0.90)
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