The helper function joins the data for the "joined" functions. All .join
variables are included in the output dataset. It is called by
get_joined_data() to process each by group separately. This reduces the
memory consumption.
get_joined_sub_data(
dataset,
dataset_add,
by_vars,
tmp_obs_nr_var,
tmp_obs_nr_left,
join_type,
first_cond_upper,
first_cond_lower,
filter_join
)Input dataset
The variables specified by the by_vars argument are expected to be in the dataset.
Additional dataset
The variables specified by the by_vars, the new_vars, the join_vars,
and the order argument are expected.
Grouping variables
The two datasets are joined by the specified variables.
Variables can be renamed by naming the element, i.e.
by_vars = exprs(<name in input dataset> = <name in additional dataset>), similar to the dplyr joins.
Permitted Values: list of variables created by exprs()
e.g. exprs(USUBJID, VISIT)
Temporary observation number
The specified variable is added to the input dataset (dataset) and the
additional dataset (dataset_add). It is set to the observation number
with respect to order. For each by group (by_vars) the observation
number starts with 1. The variable can be used in the conditions
(filter_join, first_cond_upper, first_cond_lower). It can also be
used to select consecutive observations or the last observation.
Observations to keep after joining
The argument determines which of the joined observations are kept with
respect to the original observation. For example, if join_type = "after"
is specified all observations after the original observations are kept.
For example for confirmed response or BOR in the oncology setting or
confirmed deterioration in questionnaires the confirmatory assessment must
be after the assessment. Thus join_type = "after" could be used.
Whereas, sometimes you might allow for confirmatory observations to occur
prior to the observation. For example, to identify AEs occurring on or
after seven days before a COVID AE. Thus join_type = "all" could be used.
Permitted Values: "before", "after", "all"
Condition for selecting range of data (after)
If this argument is specified, the other observations are restricted up to the first observation where the specified condition is fulfilled. If the condition is not fulfilled for any of the other observations, no observations are considered, i.e., the observation is not flagged.
This argument should be specified if filter_join contains summary
functions which should not apply to all observations but only up to the
confirmation assessment.
Condition for selecting range of data (before)
If this argument is specified, the other observations are restricted from the first observation before the current observation where the specified condition is fulfilled up to the current observation. If the condition is not fulfilled for any of the other observations, no observations are considered, i.e., the observation is not flagged.
This argument should be specified if filter_join contains summary
functions which should not apply to all observations but only from a
certain observation before the current observation up to the current
observation.
Filter for the joined dataset
The specified condition is applied to the joined dataset. Therefore
variables from both datasets dataset and dataset_add can be used.
Variables created by order or new_vars arguments can be used in the
condition.
The condition can include summary functions like all() or any(). The
joined dataset is grouped by the original observations.
Permitted Values: a condition
The input dataset (dataset) and the additional dataset (dataset_add)
are left joined by the grouping variables (by_vars). If no grouping
variables are specified, a full join is performed.
The joined dataset is restricted as specified by arguments join_type,
first_cond_upper, and first_cond_lower. See argument descriptions for
details.
The joined dataset is restricted by the filter_join condition.