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Merge an Existence Flag

Source: R/derive_merged.R
derive_var_merged_exist_flag.Rd

Adds a flag variable to the input dataset which indicates if there exists at least one observation in another dataset fulfilling a certain condition.

Note: This is a wrapper function for the more generic derive_vars_merged().

Usage

derive_var_merged_exist_flag(
  dataset,
  dataset_add,
  by_vars,
  new_var,
  condition,
  true_value = "Y",
  false_value = NA_character_,
  missing_value = NA_character_,
  filter_add = NULL
)

Arguments

dataset

Input dataset

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

dataset_add

Additional dataset

The variables specified by the by_vars argument are expected.

by_vars

Grouping variables

Permitted Values: list of variables created by exprs() e.g. exprs(USUBJID, VISIT)

new_var

New variable

The specified variable is added to the input dataset.

condition

Condition

The condition is evaluated at the additional dataset (dataset_add). For all by groups where it evaluates as TRUE at least once the new variable is set to the true value (true_value). For all by groups where it evaluates as FALSE or NA for all observations the new variable is set to the false value (false_value). The new variable is set to the missing value (missing_value) for by groups not present in the additional dataset.

true_value

True value

false_value

False value

missing_value

Values used for missing information

The new variable is set to the specified value for all by groups without observations in the additional dataset.

Permitted Value: A character scalar

filter_add

Filter for additional data

Only observations fulfilling the specified condition are taken into account for flagging. If the argument is not specified, all observations are considered.

Permitted Values: a condition

Value

The output dataset contains all observations and variables of the input dataset and additionally the variable specified for new_var derived from the additional dataset (dataset_add).

Details

  1. The additional dataset is restricted to the observations matching the filter_add condition.

  2. The new variable is added to the input dataset and set to the true value (true_value) if for the by group at least one observation exists in the (restricted) additional dataset where the condition evaluates to TRUE. It is set to the false value (false_value) if for the by group at least one observation exists and for all observations the condition evaluates to FALSE or NA. Otherwise, it is set to the missing value (missing_value).

See also

General Derivation Functions for all ADaMs that returns variable appended to dataset: derive_var_extreme_flag(), derive_var_joined_exist_flag(), derive_var_merged_ef_msrc(), derive_var_merged_summary(), derive_var_obs_number(), derive_var_relative_flag(), derive_vars_cat(), derive_vars_computed(), derive_vars_joined(), derive_vars_merged(), derive_vars_merged_lookup(), derive_vars_transposed()

Examples


library(dplyr, warn.conflicts = FALSE)

dm <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID, ~AGE,   ~AGEU,
  "PILOT01",    "DM", "01-1028",   71, "YEARS",
  "PILOT01",    "DM", "04-1127",   84, "YEARS",
  "PILOT01",    "DM", "06-1049",   60, "YEARS"
)

ae <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID,    ~AETERM,     ~AEREL,
  "PILOT01",    "AE", "01-1028", "ERYTHEMA", "POSSIBLE",
  "PILOT01",    "AE", "01-1028", "PRURITUS", "PROBABLE",
  "PILOT01",    "AE", "06-1049",  "SYNCOPE", "POSSIBLE",
  "PILOT01",    "AE", "06-1049",  "SYNCOPE", "PROBABLE"
)


derive_var_merged_exist_flag(
  dm,
  dataset_add = ae,
  by_vars = exprs(STUDYID, USUBJID),
  new_var = AERELFL,
  condition = AEREL == "PROBABLE"
) %>%
  select(STUDYID, USUBJID, AGE, AGEU, AERELFL)
#> # A tibble: 3 × 5
#>   STUDYID USUBJID   AGE AGEU  AERELFL
#>   <chr>   <chr>   <dbl> <chr> <chr>  
#> 1 PILOT01 01-1028    71 YEARS Y      
#> 2 PILOT01 04-1127    84 YEARS NA     
#> 3 PILOT01 06-1049    60 YEARS Y      

vs <- tribble(
  ~STUDYID,  ~DOMAIN,  ~USUBJID,      ~VISIT, ~VSTESTCD, ~VSSTRESN, ~VSBLFL,
  "PILOT01",    "VS", "01-1028", "SCREENING",  "HEIGHT",     177.8,      NA,
  "PILOT01",    "VS", "01-1028", "SCREENING",  "WEIGHT",     98.88,      NA,
  "PILOT01",    "VS", "01-1028",  "BASELINE",  "WEIGHT",     99.34,     "Y",
  "PILOT01",    "VS", "01-1028",    "WEEK 4",  "WEIGHT",     98.88,      NA,
  "PILOT01",    "VS", "04-1127", "SCREENING",  "HEIGHT",     165.1,      NA,
  "PILOT01",    "VS", "04-1127", "SCREENING",  "WEIGHT",     42.87,      NA,
  "PILOT01",    "VS", "04-1127",  "BASELINE",  "WEIGHT",     41.05,     "Y",
  "PILOT01",    "VS", "04-1127",    "WEEK 4",  "WEIGHT",     41.73,      NA,
  "PILOT01",    "VS", "06-1049", "SCREENING",  "HEIGHT",    167.64,      NA,
  "PILOT01",    "VS", "06-1049", "SCREENING",  "WEIGHT",     57.61,      NA,
  "PILOT01",    "VS", "06-1049",  "BASELINE",  "WEIGHT",     57.83,     "Y",
  "PILOT01",    "VS", "06-1049",    "WEEK 4",  "WEIGHT",     58.97,      NA
)
derive_var_merged_exist_flag(
  dm,
  dataset_add = vs,
  by_vars = exprs(STUDYID, USUBJID),
  filter_add = VSTESTCD == "WEIGHT" & VSBLFL == "Y",
  new_var = WTBLHIFL,
  condition = VSSTRESN > 90,
  false_value = "N",
  missing_value = "M"
) %>%
  select(STUDYID, USUBJID, AGE, AGEU, WTBLHIFL)
#> # A tibble: 3 × 5
#>   STUDYID USUBJID   AGE AGEU  WTBLHIFL
#>   <chr>   <chr>   <dbl> <chr> <chr>   
#> 1 PILOT01 01-1028    71 YEARS Y       
#> 2 PILOT01 04-1127    84 YEARS N       
#> 3 PILOT01 06-1049    60 YEARS N