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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.

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 argument are expected.

Permitted values

a dataset, i.e., a data.frame or tibble

Default value

none

by_vars

Grouping variables

Permitted values

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

Default value

none

new_var

New variable

The specified variable is added to the input dataset.

Permitted values

an unquoted symbol, e.g., AVAL

Default value

none

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.

Comparing derived numeric variables to fixed values, e.g., PCHG <= -90, may give unexpected results due to floating point representation. For details and solutions see the "Floating Point Comparisons" section in vignette("concepts_conventions").

Permitted values

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

Default value

none

true_value

True value

Permitted values

a character scalar, i.e., a character vector of length one

Default value

"Y"

false_value

False value

Permitted values

a character scalar, i.e., a character vector of length one

Default value

NA_character_

missing_value

Value used for missing information

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

Permitted values

a character scalar, i.e., a character vector of length one

Default value

NA_character_

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.

Comparing derived numeric variables to fixed values, e.g., PCHG <= -90, may give unexpected results due to floating point representation. For details and solutions see the "Floating Point Comparisons" section in vignette("concepts_conventions").

Permitted values

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

Default value

NULL

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_obs_number(), derive_var_relative_flag(), derive_vars_cat(), derive_vars_computed(), derive_vars_joined(), derive_vars_joined_summary(), derive_vars_merged(), derive_vars_merged_lookup(), derive_vars_merged_summary(), 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