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Add a Variable Flagging the First or Last Observation Within Each By Group

Source: R/derive_var_extreme_flag.R
derive_var_extreme_flag.Rd

Add a variable flagging the first or last observation within each by group

Usage 

derive_var_extreme_flag(
  dataset,
  by_vars,
  order,
  new_var,
  mode,
  true_value = "Y",
  false_value = NA_character_,
  flag_all = FALSE,
  check_type = "warning"
)

Arguments

dataset

Input dataset

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

Default value

none

by_vars

Grouping variables

Default value

none

order

Sort order

The first or last observation is determined with respect to the specified order.

For handling of NAs in sorting variables see Sort Order.

Permitted values

list of variables or functions of variables

Default value

none

new_var

Variable to add

The specified variable is added to the output dataset. It is set to the value set in true_value for the first or last observation (depending on the mode) of each by group.

Permitted values

list of name-value pairs

Default value

none

mode

Flag mode

Determines of the first or last observation is flagged.

Permitted values

"first", "last"

Default value

none

true_value

True value

The value for the specified variable new_var, applicable to the first or last observation (depending on the mode) of each by group.

Permitted values

An atomic scalar

Default value

"Y"

false_value

False value

The value for the specified variable new_var, NOT applicable to the first or last observation (depending on the mode) of each by group.

Permitted values

An atomic scalar

Default value

NA_character_

flag_all

Flag setting

A logical value where if set to TRUE, all records are flagged and no error or warning is issued if the first or last record is not unique.

Default value

FALSE

check_type

Check uniqueness?

If "warning" or "error" is specified, the specified message is issued if the observations of the input dataset are not unique with respect to the by variables and the order.

Permitted values

"none", "warning", "error"

Default value

"warning"

Value

The input dataset with the new flag variable added

Details

For each group (with respect to the variables specified for the by_vars parameter), new_var is set to "Y" for the first or last observation (with respect to the order specified for the order parameter and the flag mode specified for the mode parameter). In the case where the user wants to flag multiple records of a grouping, for example records that all happen on the same visit and time, the argument flag_all can be set to TRUE. Otherwise, new_var is set to NA. Thus, the direction of "worst" is considered fixed for all parameters in the dataset depending on the order and the mode, i.e. for every parameter the first or last record will be flagged across the whole dataset.

See also

General Derivation Functions for all ADaMs that returns variable appended to dataset: derive_var_joined_exist_flag(), derive_var_merged_ef_msrc(), derive_var_merged_exist_flag(), 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(tibble)
library(dplyr, warn.conflicts = FALSE)
example_vs <- tribble(
  ~USUBJID, ~VSTESTCD,      ~VISIT, ~VISITNUM, ~VSTPTNUM, ~VSSTRESN,
  "1001",     "DIABP", "SCREENING",         1,        10,        64,
  "1001",     "DIABP", "SCREENING",         1,        11,        66,
  "1001",     "DIABP",  "BASELINE",         2,       100,        68,
  "1001",     "DIABP",  "BASELINE",         2,       101,        68,
  "1001",     "DIABP",    "WEEK 2",         3,       200,        72,
  "1001",     "DIABP",    "WEEK 2",         3,       201,        71,
  "1001",     "DIABP",    "WEEK 4",         4,       300,        70,
  "1001",     "DIABP",    "WEEK 4",         4,       301,        70
)

# Flag last value for each patient, test, and visit, baseline observations are ignored
example_vs %>%
  restrict_derivation(
    derivation = derive_var_extreme_flag,
    args = params(
      by_vars = exprs(USUBJID, VSTESTCD, VISIT),
      order = exprs(VSTPTNUM),
      new_var = LASTFL,
      mode = "last"
    ),
    filter = VISIT != "BASELINE"
  ) %>%
  arrange(USUBJID, VSTESTCD, VISITNUM, VSTPTNUM) %>%
  select(USUBJID, VSTESTCD, VISIT, VSTPTNUM, VSSTRESN, LASTFL)
#> # A tibble: 8 × 6
#>   USUBJID VSTESTCD VISIT     VSTPTNUM VSSTRESN LASTFL
#>   <chr>   <chr>    <chr>        <dbl>    <dbl> <chr> 
#> 1 1001    DIABP    SCREENING       10       64 NA    
#> 2 1001    DIABP    SCREENING       11       66 Y     
#> 3 1001    DIABP    BASELINE       100       68 NA    
#> 4 1001    DIABP    BASELINE       101       68 NA    
#> 5 1001    DIABP    WEEK 2         200       72 NA    
#> 6 1001    DIABP    WEEK 2         201       71 Y     
#> 7 1001    DIABP    WEEK 4         300       70 NA    
#> 8 1001    DIABP    WEEK 4         301       70 Y     

# Baseline (ABLFL) examples:

input <- tribble(
  ~STUDYID, ~USUBJID,  ~PARAMCD,     ~AVISIT,                  ~ADT, ~AVAL,    ~DTYPE,
  "TEST01",  "PAT01", "PARAM01",  "BASELINE", as.Date("2021-04-27"),  15.0,        NA,
  "TEST01",  "PAT01", "PARAM01",  "BASELINE", as.Date("2021-04-25"),  14.0,        NA,
  "TEST01",  "PAT01", "PARAM01",  "BASELINE", as.Date("2021-04-23"),  15.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM01",    "WEEK 1", as.Date("2021-04-27"),  10.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM01",    "WEEK 2", as.Date("2021-04-30"),  12.0,        NA,
  "TEST01",  "PAT02", "PARAM01", "SCREENING", as.Date("2021-04-27"),  15.0, "AVERAGE",
  "TEST01",  "PAT02", "PARAM01",  "BASELINE", as.Date("2021-04-25"),  14.0, "AVERAGE",
  "TEST01",  "PAT02", "PARAM01",  "BASELINE", as.Date("2021-04-23"),  15.0, "AVERAGE",
  "TEST01",  "PAT02", "PARAM01",    "WEEK 1", as.Date("2021-04-27"),  10.0, "AVERAGE",
  "TEST01",  "PAT02", "PARAM01",    "WEEK 2", as.Date("2021-04-30"),  12.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM02", "SCREENING", as.Date("2021-04-27"),  15.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM02", "SCREENING", as.Date("2021-04-25"),  14.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM02", "SCREENING", as.Date("2021-04-23"),  15.0,        NA,
  "TEST01",  "PAT01", "PARAM02",  "BASELINE", as.Date("2021-04-27"),  10.0, "AVERAGE",
  "TEST01",  "PAT01", "PARAM02",    "WEEK 2", as.Date("2021-04-30"),  12.0,        NA,
  "TEST01",  "PAT02", "PARAM02", "SCREENING", as.Date("2021-04-27"),  15.0,        NA,
  "TEST01",  "PAT02", "PARAM02",  "BASELINE", as.Date("2021-04-25"),  14.0,        NA,
  "TEST01",  "PAT02", "PARAM02",    "WEEK 1", as.Date("2021-04-23"),  15.0,        NA,
  "TEST01",  "PAT02", "PARAM02",    "WEEK 1", as.Date("2021-04-27"),  10.0,        NA,
  "TEST01",  "PAT02", "PARAM02",  "BASELINE", as.Date("2021-04-30"),  12.0,        NA
)

# Last observation
restrict_derivation(
  input,
  derivation = derive_var_extreme_flag,
  args = params(
    by_vars = exprs(USUBJID, PARAMCD),
    order = exprs(ADT),
    new_var = ABLFL,
    mode = "last"
  ),
  filter = AVISIT == "BASELINE"
)
#> # A tibble: 20 × 8
#>    STUDYID USUBJID PARAMCD AVISIT    ADT         AVAL DTYPE   ABLFL
#>    <chr>   <chr>   <chr>   <chr>     <date>     <dbl> <chr>   <chr>
#>  1 TEST01  PAT01   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  2 TEST01  PAT01   PARAM01 BASELINE  2021-04-25    14 NA      NA   
#>  3 TEST01  PAT01   PARAM01 BASELINE  2021-04-27    15 NA      Y    
#>  4 TEST01  PAT01   PARAM02 BASELINE  2021-04-27    10 AVERAGE Y    
#>  5 TEST01  PAT02   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  6 TEST01  PAT02   PARAM01 BASELINE  2021-04-25    14 AVERAGE Y    
#>  7 TEST01  PAT02   PARAM02 BASELINE  2021-04-25    14 NA      NA   
#>  8 TEST01  PAT02   PARAM02 BASELINE  2021-04-30    12 NA      Y    
#>  9 TEST01  PAT01   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 10 TEST01  PAT01   PARAM01 WEEK 2    2021-04-30    12 NA      NA   
#> 11 TEST01  PAT02   PARAM01 SCREENING 2021-04-27    15 AVERAGE NA   
#> 12 TEST01  PAT02   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 13 TEST01  PAT02   PARAM01 WEEK 2    2021-04-30    12 AVERAGE NA   
#> 14 TEST01  PAT01   PARAM02 SCREENING 2021-04-27    15 AVERAGE NA   
#> 15 TEST01  PAT01   PARAM02 SCREENING 2021-04-25    14 AVERAGE NA   
#> 16 TEST01  PAT01   PARAM02 SCREENING 2021-04-23    15 NA      NA   
#> 17 TEST01  PAT01   PARAM02 WEEK 2    2021-04-30    12 NA      NA   
#> 18 TEST01  PAT02   PARAM02 SCREENING 2021-04-27    15 NA      NA   
#> 19 TEST01  PAT02   PARAM02 WEEK 1    2021-04-23    15 NA      NA   
#> 20 TEST01  PAT02   PARAM02 WEEK 1    2021-04-27    10 NA      NA   

# Worst observation - Direction = High
restrict_derivation(
  input,
  derivation = derive_var_extreme_flag,
  args = params(
    by_vars = exprs(USUBJID, PARAMCD),
    order = exprs(AVAL, ADT),
    new_var = ABLFL,
    mode = "last"
  ),
  filter = AVISIT == "BASELINE"
)
#> # A tibble: 20 × 8
#>    STUDYID USUBJID PARAMCD AVISIT    ADT         AVAL DTYPE   ABLFL
#>    <chr>   <chr>   <chr>   <chr>     <date>     <dbl> <chr>   <chr>
#>  1 TEST01  PAT01   PARAM01 BASELINE  2021-04-25    14 NA      NA   
#>  2 TEST01  PAT01   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  3 TEST01  PAT01   PARAM01 BASELINE  2021-04-27    15 NA      Y    
#>  4 TEST01  PAT01   PARAM02 BASELINE  2021-04-27    10 AVERAGE Y    
#>  5 TEST01  PAT02   PARAM01 BASELINE  2021-04-25    14 AVERAGE NA   
#>  6 TEST01  PAT02   PARAM01 BASELINE  2021-04-23    15 AVERAGE Y    
#>  7 TEST01  PAT02   PARAM02 BASELINE  2021-04-30    12 NA      NA   
#>  8 TEST01  PAT02   PARAM02 BASELINE  2021-04-25    14 NA      Y    
#>  9 TEST01  PAT01   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 10 TEST01  PAT01   PARAM01 WEEK 2    2021-04-30    12 NA      NA   
#> 11 TEST01  PAT02   PARAM01 SCREENING 2021-04-27    15 AVERAGE NA   
#> 12 TEST01  PAT02   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 13 TEST01  PAT02   PARAM01 WEEK 2    2021-04-30    12 AVERAGE NA   
#> 14 TEST01  PAT01   PARAM02 SCREENING 2021-04-27    15 AVERAGE NA   
#> 15 TEST01  PAT01   PARAM02 SCREENING 2021-04-25    14 AVERAGE NA   
#> 16 TEST01  PAT01   PARAM02 SCREENING 2021-04-23    15 NA      NA   
#> 17 TEST01  PAT01   PARAM02 WEEK 2    2021-04-30    12 NA      NA   
#> 18 TEST01  PAT02   PARAM02 SCREENING 2021-04-27    15 NA      NA   
#> 19 TEST01  PAT02   PARAM02 WEEK 1    2021-04-23    15 NA      NA   
#> 20 TEST01  PAT02   PARAM02 WEEK 1    2021-04-27    10 NA      NA   

# Worst observation - Direction = Lo
restrict_derivation(
  input,
  derivation = derive_var_extreme_flag,
  args = params(
    by_vars = exprs(USUBJID, PARAMCD),
    order = exprs(desc(AVAL), ADT),
    new_var = ABLFL,
    mode = "last"
  ),
  filter = AVISIT == "BASELINE"
)
#> # A tibble: 20 × 8
#>    STUDYID USUBJID PARAMCD AVISIT    ADT         AVAL DTYPE   ABLFL
#>    <chr>   <chr>   <chr>   <chr>     <date>     <dbl> <chr>   <chr>
#>  1 TEST01  PAT01   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  2 TEST01  PAT01   PARAM01 BASELINE  2021-04-27    15 NA      NA   
#>  3 TEST01  PAT01   PARAM01 BASELINE  2021-04-25    14 NA      Y    
#>  4 TEST01  PAT01   PARAM02 BASELINE  2021-04-27    10 AVERAGE Y    
#>  5 TEST01  PAT02   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  6 TEST01  PAT02   PARAM01 BASELINE  2021-04-25    14 AVERAGE Y    
#>  7 TEST01  PAT02   PARAM02 BASELINE  2021-04-25    14 NA      NA   
#>  8 TEST01  PAT02   PARAM02 BASELINE  2021-04-30    12 NA      Y    
#>  9 TEST01  PAT01   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 10 TEST01  PAT01   PARAM01 WEEK 2    2021-04-30    12 NA      NA   
#> 11 TEST01  PAT02   PARAM01 SCREENING 2021-04-27    15 AVERAGE NA   
#> 12 TEST01  PAT02   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 13 TEST01  PAT02   PARAM01 WEEK 2    2021-04-30    12 AVERAGE NA   
#> 14 TEST01  PAT01   PARAM02 SCREENING 2021-04-27    15 AVERAGE NA   
#> 15 TEST01  PAT01   PARAM02 SCREENING 2021-04-25    14 AVERAGE NA   
#> 16 TEST01  PAT01   PARAM02 SCREENING 2021-04-23    15 NA      NA   
#> 17 TEST01  PAT01   PARAM02 WEEK 2    2021-04-30    12 NA      NA   
#> 18 TEST01  PAT02   PARAM02 SCREENING 2021-04-27    15 NA      NA   
#> 19 TEST01  PAT02   PARAM02 WEEK 1    2021-04-23    15 NA      NA   
#> 20 TEST01  PAT02   PARAM02 WEEK 1    2021-04-27    10 NA      NA   

# Average observation
restrict_derivation(
  input,
  derivation = derive_var_extreme_flag,
  args = params(
    by_vars = exprs(USUBJID, PARAMCD),
    order = exprs(ADT, desc(AVAL)),
    new_var = ABLFL,
    mode = "last"
  ),
  filter = AVISIT == "BASELINE" & DTYPE == "AVERAGE"
)
#> # A tibble: 20 × 8
#>    STUDYID USUBJID PARAMCD AVISIT    ADT         AVAL DTYPE   ABLFL
#>    <chr>   <chr>   <chr>   <chr>     <date>     <dbl> <chr>   <chr>
#>  1 TEST01  PAT01   PARAM01 BASELINE  2021-04-23    15 AVERAGE Y    
#>  2 TEST01  PAT01   PARAM02 BASELINE  2021-04-27    10 AVERAGE Y    
#>  3 TEST01  PAT02   PARAM01 BASELINE  2021-04-23    15 AVERAGE NA   
#>  4 TEST01  PAT02   PARAM01 BASELINE  2021-04-25    14 AVERAGE Y    
#>  5 TEST01  PAT01   PARAM01 BASELINE  2021-04-27    15 NA      NA   
#>  6 TEST01  PAT01   PARAM01 BASELINE  2021-04-25    14 NA      NA   
#>  7 TEST01  PAT01   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#>  8 TEST01  PAT01   PARAM01 WEEK 2    2021-04-30    12 NA      NA   
#>  9 TEST01  PAT02   PARAM01 SCREENING 2021-04-27    15 AVERAGE NA   
#> 10 TEST01  PAT02   PARAM01 WEEK 1    2021-04-27    10 AVERAGE NA   
#> 11 TEST01  PAT02   PARAM01 WEEK 2    2021-04-30    12 AVERAGE NA   
#> 12 TEST01  PAT01   PARAM02 SCREENING 2021-04-27    15 AVERAGE NA   
#> 13 TEST01  PAT01   PARAM02 SCREENING 2021-04-25    14 AVERAGE NA   
#> 14 TEST01  PAT01   PARAM02 SCREENING 2021-04-23    15 NA      NA   
#> 15 TEST01  PAT01   PARAM02 WEEK 2    2021-04-30    12 NA      NA   
#> 16 TEST01  PAT02   PARAM02 SCREENING 2021-04-27    15 NA      NA   
#> 17 TEST01  PAT02   PARAM02 BASELINE  2021-04-25    14 NA      NA   
#> 18 TEST01  PAT02   PARAM02 WEEK 1    2021-04-23    15 NA      NA   
#> 19 TEST01  PAT02   PARAM02 WEEK 1    2021-04-27    10 NA      NA   
#> 20 TEST01  PAT02   PARAM02 BASELINE  2021-04-30    12 NA      NA   

# OCCURDS Examples
example_ae <- tribble(
  ~USUBJID,         ~AEBODSYS,    ~AEDECOD,   ~AESEV, ~AESTDY, ~AESEQ,
  "1015", "GENERAL DISORDERS",  "ERYTHEMA",   "MILD",       2,      1,
  "1015", "GENERAL DISORDERS",  "PRURITUS",   "MILD",       2,      2,
  "1015",      "GI DISORDERS", "DIARRHOEA",   "MILD",       8,      3,
  "1023", "CARDIAC DISORDERS",  "AV BLOCK",   "MILD",      22,      4,
  "1023",    "SKIN DISORDERS",  "ERYTHEMA",   "MILD",       3,      1,
  "1023",    "SKIN DISORDERS",  "ERYTHEMA", "SEVERE",       5,      2,
  "1023",    "SKIN DISORDERS",  "ERYTHEMA",   "MILD",       8,      3
)

# Most severe AE first occurrence per patient
example_ae %>%
  mutate(
    TEMP_AESEVN =
      as.integer(factor(AESEV, levels = c("SEVERE", "MODERATE", "MILD")))
  ) %>%
  derive_var_extreme_flag(
    new_var = AOCCIFL,
    by_vars = exprs(USUBJID),
    order = exprs(TEMP_AESEVN, AESTDY, AESEQ),
    mode = "first"
  ) %>%
  arrange(USUBJID, AESTDY, AESEQ) %>%
  select(USUBJID, AEDECOD, AESEV, AESTDY, AESEQ, AOCCIFL)
#> # A tibble: 7 × 6
#>   USUBJID AEDECOD   AESEV  AESTDY AESEQ AOCCIFL
#>   <chr>   <chr>     <chr>   <dbl> <dbl> <chr>  
#> 1 1015    ERYTHEMA  MILD        2     1 Y      
#> 2 1015    PRURITUS  MILD        2     2 NA     
#> 3 1015    DIARRHOEA MILD        8     3 NA     
#> 4 1023    ERYTHEMA  MILD        3     1 NA     
#> 5 1023    ERYTHEMA  SEVERE      5     2 Y      
#> 6 1023    ERYTHEMA  MILD        8     3 NA     
#> 7 1023    AV BLOCK  MILD       22     4 NA     

# Most severe AE first occurrence per patient (flag all cases)
example_ae %>%
  mutate(
    TEMP_AESEVN =
      as.integer(factor(AESEV, levels = c("SEVERE", "MODERATE", "MILD")))
  ) %>%
  derive_var_extreme_flag(
    new_var = AOCCIFL,
    by_vars = exprs(USUBJID),
    order = exprs(TEMP_AESEVN, AESTDY),
    mode = "first",
    flag_all = TRUE
  ) %>%
  arrange(USUBJID, AESTDY) %>%
  select(USUBJID, AEDECOD, AESEV, AESTDY, AOCCIFL)
#> # A tibble: 7 × 5
#>   USUBJID AEDECOD   AESEV  AESTDY AOCCIFL
#>   <chr>   <chr>     <chr>   <dbl> <chr>  
#> 1 1015    ERYTHEMA  MILD        2 Y      
#> 2 1015    PRURITUS  MILD        2 Y      
#> 3 1015    DIARRHOEA MILD        8 NA     
#> 4 1023    ERYTHEMA  MILD        3 NA     
#> 5 1023    ERYTHEMA  SEVERE      5 Y      
#> 6 1023    ERYTHEMA  MILD        8 NA     
#> 7 1023    AV BLOCK  MILD       22 NA     

# Most severe AE first occurrence per patient per body system
example_ae %>%
  mutate(
    TEMP_AESEVN =
      as.integer(factor(AESEV, levels = c("SEVERE", "MODERATE", "MILD")))
  ) %>%
  derive_var_extreme_flag(
    new_var = AOCCSIFL,
    by_vars = exprs(USUBJID, AEBODSYS),
    order = exprs(TEMP_AESEVN, AESTDY, AESEQ),
    mode = "first"
  ) %>%
  arrange(USUBJID, AESTDY, AESEQ) %>%
  select(USUBJID, AEBODSYS, AESEV, AESTDY, AOCCSIFL)
#> # A tibble: 7 × 5
#>   USUBJID AEBODSYS          AESEV  AESTDY AOCCSIFL
#>   <chr>   <chr>             <chr>   <dbl> <chr>   
#> 1 1015    GENERAL DISORDERS MILD        2 Y       
#> 2 1015    GENERAL DISORDERS MILD        2 NA      
#> 3 1015    GI DISORDERS      MILD        8 Y       
#> 4 1023    SKIN DISORDERS    MILD        3 NA      
#> 5 1023    SKIN DISORDERS    SEVERE      5 Y       
#> 6 1023    SKIN DISORDERS    MILD        8 NA      
#> 7 1023    CARDIAC DISORDERS MILD       22 Y