h_response_biomarkers_subgroups {tern}R Documentation

Helper functions for tabulating biomarker effects on binary response by subgroup

Description

[Stable]

Helper functions which are documented here separately to not confuse the user when reading about the user-facing functions.

Usage

h_rsp_to_logistic_variables(variables, biomarker)

h_logistic_mult_cont_df(variables, data, control = control_logistic())

Arguments

variables

(named list of string)
list of additional analysis variables.

biomarker

(string)
the name of the biomarker variable.

data

(data.frame)
the dataset containing the variables to summarize.

control

(named list)
controls for the response definition and the confidence level produced by control_logistic().

Value

Functions

Examples

library(dplyr)
library(forcats)

adrs <- tern_ex_adrs
adrs_labels <- formatters::var_labels(adrs)

adrs_f <- adrs %>%
  filter(PARAMCD == "BESRSPI") %>%
  mutate(rsp = AVALC == "CR")
formatters::var_labels(adrs_f) <- c(adrs_labels, "Response")

# This is how the variable list is converted internally.
h_rsp_to_logistic_variables(
  variables = list(
    rsp = "RSP",
    covariates = c("A", "B"),
    strata = "D"
  ),
  biomarker = "AGE"
)

# For a single population, estimate separately the effects
# of two biomarkers.
df <- h_logistic_mult_cont_df(
  variables = list(
    rsp = "rsp",
    biomarkers = c("BMRKR1", "AGE"),
    covariates = "SEX"
  ),
  data = adrs_f
)
df

# If the data set is empty, still the corresponding rows with missings are returned.
h_coxreg_mult_cont_df(
  variables = list(
    rsp = "rsp",
    biomarkers = c("BMRKR1", "AGE"),
    covariates = "SEX",
    strata = "STRATA1"
  ),
  data = adrs_f[NULL, ]
)


[Package tern version 0.9.9 Index]