sdtm_assign() is an internal function packing the same functionality as
assign_no_ct() and assign_ct() together but aimed at developers only.
As a user please use either assign_no_ct() or assign_ct().
sdtm_assign(
tgt_dat = NULL,
tgt_var,
raw_dat,
raw_var,
ct_spec = NULL,
ct_clst = NULL,
id_vars = oak_id_vars()
)The returned data set depends on the value of tgt_dat:
If no target dataset is supplied, meaning that tgt_dat defaults to
NULL, then the returned data set is raw_dat, selected for the variables
indicated in id_vars, and a new extra column: the derived variable, as
indicated in tgt_var.
If the target dataset is provided, then it is merged with the raw data set
raw_dat by the variables indicated in id_vars, with a new column: the
derived variable, as indicated in tgt_var.
Target dataset: a data frame to be merged against raw_dat by
the variables indicated in id_vars. This parameter is optional, see
section Value for how the output changes depending on this argument value.
The target SDTM variable: a single string indicating the name of variable to be derived.
The raw dataset (dataframe); must include the
variables passed in id_vars and raw_var.
The raw variable: a single string indicating the name of the
raw variable in raw_dat.
Study controlled terminology specification: a dataframe with a
minimal set of columns, see ct_spec_vars() for details. This parameter is
optional, if left as NULL no controlled terminology recoding is applied.
A codelist code indicating which subset of the controlled
terminology to apply in the derivation. This parameter is optional, if left
as NULL, all possible recodings in ct_spec are attempted.
Key variables to be used in the join between the raw dataset
(raw_dat) and the target data set (tgt_dat).