get_joined_sub_data: Join Data for "joined" functions

Description

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.

Usage

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
)

Arguments

dataset

Input dataset

The variables specified by the by_vars argument are expected to be in the dataset.

Permitted values: a dataset, i.e., a data.frame or tibble

Default value

none

dataset_add

Additional dataset

The variables specified by the by_vars, the new_vars, the join_vars, and the order argument are expected.

Permitted values: a dataset, i.e., a data.frame or tibble

Default value

none

by_vars

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)

Default value

NULL

tmp_obs_nr_var

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.

Permitted values: an unquoted symbol, e.g., AVAL

Default value

NULL

tmp_obs_nr_left

Temporary observation number for dataset

The specified variable has to be in the input dataset (dataset) and has to be a unique key.

Default value: none

join_type

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"

Default value

none

first_cond_upper

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.

Permitted values: an unquoted condition, e.g., AVISIT == "BASELINE"

Default value

NULL

first_cond_lower

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.

Permitted values: an unquoted condition, e.g., AVISIT == "BASELINE"

Default value

NULL

filter_join

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: an unquoted condition, e.g., AVISIT == "BASELINE"

Default value

NULL

Details

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.