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Expression: Arm Preparation

Source: R/utils.R
prepare_arm.Rd

The function generate the standard expression for pre-processing of dataset in teal module applications. This is especially of interest when the same preprocessing steps needs to be applied similarly to several datasets (e.g. ADSL and ADRS).

Usage 

prepare_arm(
  dataname,
  arm_var,
  ref_arm,
  comp_arm,
  compare_arm = !is.null(ref_arm),
  ref_arm_val = paste(ref_arm, collapse = "/"),
  drop = TRUE
)

Arguments

dataname

(character)
analysis data used in teal module.

arm_var

(character)
variable names that can be used as arm_var.

ref_arm

(character)
the level of reference arm in case of arm comparison.

comp_arm

(character)
the level of comparison arm in case of arm comparison.

compare_arm

(logical)
triggers the comparison between study arms.

ref_arm_val

(character)
replacement name for the reference level.

drop

(logical)
drop the unused variable levels.

Value

a call

Details

In teal.modules.clinical, the user interface includes manipulation of the study arms. Classically: the arm variable itself (e.g. ARM, ACTARM), the reference arm (0 or more), the comparison arm (1 or more) and the possibility to combine comparison arms.

Note that when no arms should be compared with each other, then the produced expression is reduced to optionally dropping non-represented levels of the arm.

When comparing arms, the pre-processing includes three steps:

  1. Filtering of the dataset to retain only the arms of interest (reference and comparison).

  2. Optional, if more than one arm is designated as reference they are combined into a single level.

  3. The reference is explicitly reassigned and the non-represented levels of arm are dropped.

Examples 

prepare_arm(
  dataname = "adrs",
  arm_var = "ARMCD",
  ref_arm = "ARM A",
  comp_arm = c("ARM B", "ARM C")
)
#> adrs %>% dplyr::filter(ARMCD %in% c("ARM A", "ARM B", "ARM C")) %>% 
#>     dplyr::mutate(ARMCD = stats::relevel(ARMCD, ref = "ARM A")) %>% 
#>     dplyr::mutate(ARMCD = droplevels(ARMCD))

prepare_arm(
  dataname = "adsl",
  arm_var = "ARMCD",
  ref_arm = c("ARM B", "ARM C"),
  comp_arm = "ARM A"
)
#> adsl %>% dplyr::filter(ARMCD %in% c("ARM B", "ARM C", "ARM A")) %>% 
#>     dplyr::mutate(ARMCD = combine_levels(ARMCD, levels = c("ARM B", 
#>         "ARM C"), new_level = "ARM B/ARM C")) %>% dplyr::mutate(ARMCD = stats::relevel(ARMCD, 
#>     ref = "ARM B/ARM C")) %>% dplyr::mutate(ARMCD = droplevels(ARMCD))