h_survival_biomarkers_subgroups | R Documentation |
Helper functions which are documented here separately to not confuse the user when reading about the user-facing functions.
h_surv_to_coxreg_variables(variables, biomarker)
h_coxreg_mult_cont_df(variables, data, control = control_coxreg())
variables |
(named |
biomarker |
( |
data |
( |
control |
( |
h_surv_to_coxreg_variables()
returns a named list
of elements time
, event
, arm
,
covariates
, and strata
.
h_coxreg_mult_cont_df()
returns a data.frame
containing estimates and statistics for the selected biomarkers.
h_surv_to_coxreg_variables()
: Helps with converting the "survival" function variable list
to the "Cox regression" variable list. The reason is that currently there is an inconsistency between the variable
names accepted by extract_survival_subgroups()
and fit_coxreg_multivar()
.
h_coxreg_mult_cont_df()
: Prepares estimates for number of events, patients and median survival
times, as well as hazard ratio estimates, confidence intervals and p-values, for multiple biomarkers
in a given single data set.
variables
corresponds to names of variables found in data
, passed as a named list and requires elements
tte
, is_event
, biomarkers
(vector of continuous biomarker variables) and optionally subgroups
and strata
.
library(dplyr)
library(forcats)
adtte <- tern_ex_adtte
# Save variable labels before data processing steps.
adtte_labels <- formatters::var_labels(adtte, fill = FALSE)
adtte_f <- adtte %>%
filter(PARAMCD == "OS") %>%
mutate(
AVALU = as.character(AVALU),
is_event = CNSR == 0
)
labels <- c("AVALU" = adtte_labels[["AVALU"]], "is_event" = "Event Flag")
formatters::var_labels(adtte_f)[names(labels)] <- labels
# This is how the variable list is converted internally.
h_surv_to_coxreg_variables(
variables = list(
tte = "AVAL",
is_event = "EVNT",
covariates = c("A", "B"),
strata = "D"
),
biomarker = "AGE"
)
# For a single population, estimate separately the effects
# of two biomarkers.
df <- h_coxreg_mult_cont_df(
variables = list(
tte = "AVAL",
is_event = "is_event",
biomarkers = c("BMRKR1", "AGE"),
covariates = "SEX",
strata = c("STRATA1", "STRATA2")
),
data = adtte_f
)
df
# If the data set is empty, still the corresponding rows with missings are returned.
h_coxreg_mult_cont_df(
variables = list(
tte = "AVAL",
is_event = "is_event",
biomarkers = c("BMRKR1", "AGE"),
covariates = "REGION1",
strata = c("STRATA1", "STRATA2")
),
data = adtte_f[NULL, ]
)
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