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Derive Variables by Transposing and Merging a Second Dataset

Source: R/derive_vars_transposed.R
derive_vars_transposed.Rd

Adds variables from a vertical dataset after transposing it into a wide one.

Usage 

derive_vars_transposed(
  dataset,
  dataset_merge,
  by_vars,
  id_vars = NULL,
  key_var,
  value_var,
  filter = NULL,
  relationship = NULL
)

Arguments

dataset

Input dataset

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

Default value

none

dataset_merge

Dataset to transpose and merge

The variables specified by the by_vars, id_vars, key_var and value_var arguments are expected. The variables by_vars, id_vars, key_var have to be a unique key.

Default value

none

by_vars

Grouping variables

Keys used to merge dataset_merge with dataset.

Default value

none

id_vars

ID variables

Variables (excluding by_vars and key_var) that uniquely identify each observation in dataset_merge.

Default value

NULL

key_var

The variable of dataset_merge containing the names of the transposed variables

Default value

none

value_var

The variable of dataset_merge containing the values of the transposed variables

Default value

none

filter

Expression used to restrict the records of dataset_merge prior to transposing

Default value

NULL

relationship

Expected merge-relationship between the by_vars variable(s) in dataset and dataset_merge (after transposition)

This argument is passed to the dplyr::left_join() function. See https://dplyr.tidyverse.org/reference/mutate-joins.html#arguments for more details.

Permitted values

"one-to-one", "one-to-many", "many-to-one", "many-to-many", NULL

Default value

NULL

Value

The input dataset with transposed variables from dataset_merge added

Details

  1. The records from the dataset to transpose and merge (dataset_merge) are restricted to those matching the filter condition, if provided.

  2. The records from dataset_merge are checked to ensure they are uniquely identified using by_vars, id_vars and key_var.

  3. dataset_merge is transposed (from "tall" to "wide"), with new variables added whose names come from key_var and values come from value_var.

  4. The transposed dataset is merged with the input dataset using by_vars as keys. If a relationship has been provided, this merge must satisfy the relationship, otherwise an error is thrown.

Note that unlike other derive_vars_*() functions, the final step may cause new records to be added to the input dataset. The relationship argument can be specified to ensure this does not happen inadvertently.

See also

derive_vars_atc()

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_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_joined_summary(), derive_vars_merged(), derive_vars_merged_lookup()

Examples 

library(tibble)
library(dplyr, warn.conflicts = FALSE)

# Adding ATC classes to CM using FACM
cm <- tribble(
  ~USUBJID,       ~CMGRPID, ~CMREFID,  ~CMDECOD,
  "BP40257-1001", "14",     "1192056", "PARACETAMOL",
  "BP40257-1001", "18",     "2007001", "SOLUMEDROL",
  "BP40257-1002", "19",     "2791596", "SPIRONOLACTONE"
)
facm <- tribble(
  ~USUBJID,       ~FAGRPID, ~FAREFID,  ~FATESTCD,  ~FASTRESC,
  "BP40257-1001", "1",      "1192056", "CMATC1CD", "N",
  "BP40257-1001", "1",      "1192056", "CMATC2CD", "N02",
  "BP40257-1001", "1",      "1192056", "CMATC3CD", "N02B",
  "BP40257-1001", "1",      "1192056", "CMATC4CD", "N02BE",
  "BP40257-1001", "1",      "2007001", "CMATC1CD", "D",
  "BP40257-1001", "1",      "2007001", "CMATC2CD", "D10",
  "BP40257-1001", "1",      "2007001", "CMATC3CD", "D10A",
  "BP40257-1001", "1",      "2007001", "CMATC4CD", "D10AA",
  "BP40257-1001", "2",      "2007001", "CMATC1CD", "D",
  "BP40257-1001", "2",      "2007001", "CMATC2CD", "D07",
  "BP40257-1001", "2",      "2007001", "CMATC3CD", "D07A",
  "BP40257-1001", "2",      "2007001", "CMATC4CD", "D07AA",
  "BP40257-1001", "3",      "2007001", "CMATC1CD", "H",
  "BP40257-1001", "3",      "2007001", "CMATC2CD", "H02",
  "BP40257-1001", "3",      "2007001", "CMATC3CD", "H02A",
  "BP40257-1001", "3",      "2007001", "CMATC4CD", "H02AB",
  "BP40257-1002", "1",      "2791596", "CMATC1CD", "C",
  "BP40257-1002", "1",      "2791596", "CMATC2CD", "C03",
  "BP40257-1002", "1",      "2791596", "CMATC3CD", "C03D",
  "BP40257-1002", "1",      "2791596", "CMATC4CD", "C03DA"
)

cm %>%
  derive_vars_transposed(
    dataset_merge = facm,
    by_vars = exprs(USUBJID, CMREFID = FAREFID),
    id_vars = exprs(FAGRPID),
    key_var = FATESTCD,
    value_var = FASTRESC
  ) %>%
  select(USUBJID, CMDECOD, starts_with("CMATC"))
#> # A tibble: 5 × 6
#>   USUBJID      CMDECOD        CMATC1CD CMATC2CD CMATC3CD CMATC4CD
#>   <chr>        <chr>          <chr>    <chr>    <chr>    <chr>   
#> 1 BP40257-1001 PARACETAMOL    N        N02      N02B     N02BE   
#> 2 BP40257-1001 SOLUMEDROL     D        D10      D10A     D10AA   
#> 3 BP40257-1001 SOLUMEDROL     D        D07      D07A     D07AA   
#> 4 BP40257-1001 SOLUMEDROL     H        H02      H02A     H02AB   
#> 5 BP40257-1002 SPIRONOLACTONE C        C03      C03D     C03DA   

# Note: the `id_vars` argument here is needed to uniquely identify
# rows of dataset_merge and avoid duplicates-related errors.
# Compare the above call to when `id_vars = NULL`:

try(
  cm %>%
    derive_vars_transposed(
      dataset_merge = facm,
      by_vars = exprs(USUBJID, CMREFID = FAREFID),
      id_vars = NULL,
      key_var = FATESTCD,
      value_var = FASTRESC
    )
)
#> Error in signal_duplicate_records(dataset_merge, by_vars = c(by_vars,  : 
#>   Dataset `dataset_merge` contains duplicate records with respect to
#> `USUBJID`, `FAREFID`, and `FATESTCD`
#> Please check data and `by_vars`, `id_vars`, and `key_var` arguments.
#> ℹ Run `admiral::get_duplicates_dataset()` to access the duplicate records