Vectorised if-else

if_else() is a survey-aware version of dplyr::if_else() that applies a binary condition element-wise: true values are used where condition is TRUE, false values where it is FALSE, and missing values where it is NA.

Compared to base ifelse(), this function is stricter about types: true, false, and missing must be compatible and will be cast to their common type.

When any of .label, .value_labels, or .description are supplied, output label metadata is written to @metadata after mutate(). When none of these arguments are used, the output is identical to dplyr::if_else().

For more than two conditions, see case_when().

Usage

if_else(
  condition,
  true,
  false,
  missing = NULL,
  ...,
  ptype = NULL,
  .label = NULL,
  .value_labels = NULL,
  .description = NULL
)

Arguments

condition: A logical vector.
true, false: Vectors to use for TRUE and FALSE values of condition. Both are recycled to the size of condition and cast to their common type.
missing: If not NULL, used as the value for NA values of condition. Follows the same size and type rules as true and false.
...: These dots are for future extensions and must be empty.
ptype: An optional prototype declaring the desired output type. Overrides the common type of true, false, and missing.
.label: character(1) or NULL. Variable label stored in @metadata@variable_labels after mutate().
.value_labels: Named vector or NULL. Value labels stored in @metadata@value_labels. Names are the label strings; values are the data values.
.description: character(1) or NULL. Plain-language description of how the variable was created. Stored in @metadata@transformations[[col]]$description after mutate().

Value

A vector the same size as condition and the common type of true, false, and missing. If .label or .value_labels are supplied, returns a haven_labelled vector; otherwise returns the same type as the common type of the inputs.

Examples


library(surveycore)
library(surveytidy)
ns_wave1_svy <- as_survey_nonprob(ns_wave1, weights = weight)

# ---------------------------------------------------------------------
# Basic if_else — identical to dplyr::if_else() -----------------------
# ---------------------------------------------------------------------

new <- ns_wave1_svy |>
  mutate(senior = if_else(age >= 65, "Senior (65+)", "Non-senior")) |>
  select(age, senior)

new
#> 
#> ── Survey Design ───────────────────────────────────────────────────────────────
#> <survey_nonprob> (calibrated / non-probability) [experimental]
#> Sample size: 6422
#> 
#> # A tibble: 6,422 × 2
#>      age senior    
#>    <dbl> <chr>     
#>  1    37 Non-senior
#>  2    45 Non-senior
#>  3    24 Non-senior
#>  4    26 Non-senior
#>  5    60 Non-senior
#>  6    55 Non-senior
#>  7    37 Non-senior
#>  8    46 Non-senior
#>  9    60 Non-senior
#> 10    32 Non-senior
#> # ℹ 6,412 more rows
#> 
#> ℹ Design variables preserved but hidden: weight.
#> ℹ Use `print(x, full = TRUE)` to show all variables.

# By default, no metadata is attached
new@metadata
#> <surveycore::survey_metadata>
#>  @ variable_labels  :List of 2
#>  .. $ age   : chr "What is your age? Provided by LUCID. Response is an integer value 18 or ..."
#>  .. $ weight: chr "Survey weight, continuous value from 0-5"
#>  @ value_labels     : Named list()
#>  @ question_prefaces: Named list()
#>  @ notes            : list()
#>  @ universe         : list()
#>  @ missing_codes    : list()
#>  @ transformations  :List of 1
#>  .. $ senior: chr "if_else(age >= 65, \"Senior (65+)\", \"Non-senior\")"
#>  @ weighting_history: list()


# ---- Handle missing values ----

# Use missing = to specify the output value when condition is NA
new <- ns_wave1_svy |>
  mutate(
    dem = if_else(pid3 == 1, "Democrat", "Non-Democrat", missing = "Unknown")
  ) |>
  select(pid3, dem)

new
#> 
#> ── Survey Design ───────────────────────────────────────────────────────────────
#> <survey_nonprob> (calibrated / non-probability) [experimental]
#> Sample size: 6422
#> 
#> # A tibble: 6,422 × 2
#>     pid3 dem         
#>    <dbl> <chr>       
#>  1     1 Democrat    
#>  2     1 Democrat    
#>  3     1 Democrat    
#>  4     3 Non-Democrat
#>  5     2 Non-Democrat
#>  6     1 Democrat    
#>  7     4 Non-Democrat
#>  8     2 Non-Democrat
#>  9     2 Non-Democrat
#> 10     1 Democrat    
#> # ℹ 6,412 more rows
#> 
#> ℹ Design variables preserved but hidden: weight.
#> ℹ Use `print(x, full = TRUE)` to show all variables.


# ---------------------------------------------------------------------
# Set metadata --------------------------------------------------------
# ---------------------------------------------------------------------

# ---- Variable label ----

new <- ns_wave1_svy |>
  mutate(
    senior = if_else(
      age >= 65,
      "Senior (65+)",
      "Non-senior",
      .label = "Senior citizen (age 65+)"
    )
  ) |>
  select(age, senior)
#> Error in dplyr::mutate(base_data, ..., .keep = .keep): ℹ In argument: `senior = if_else(age >= 65, "Senior (65+)",
#>   "Non-senior", .label = "Senior citizen (age 65+)")`.
#> Caused by error in `if_else()`:
#> ! `...` must be empty.
#> ✖ Problematic argument:
#> • .label = "Senior citizen (age 65+)"

new@metadata@variable_labels
#> $pid3
#> [1] "3-category party ID"
#> 
#> $weight
#> [1] "Survey weight, continuous value from 0-5"
#> 


# ---- Value labels ----

# Use integer codes for the output and add value labels to document them
new <- ns_wave1_svy |>
  mutate(
    senior = if_else(
      age >= 65,
      true = 1L,
      false = 0L,
      .label = "Senior citizen (age 65+)",
      .value_labels = c("Senior (65+)" = 1, "Non-senior" = 0)
    )
  ) |>
  select(age, senior)
#> Error in dplyr::mutate(base_data, ..., .keep = .keep): ℹ In argument: `senior = if_else(...)`.
#> Caused by error in `if_else()`:
#> ! `...` must be empty.
#> ✖ Problematic arguments:
#> • .label = "Senior citizen (age 65+)"
#> • .value_labels = c(`Senior (65+)` = 1, `Non-senior` = 0)

new@metadata@value_labels
#> $pid3
#>       Democrat     Republican    Independent Something else 
#>              1              2              3              4 
#> 


# ---- Transformation ----

new <- ns_wave1_svy |>
  mutate(
    senior = if_else(
      age >= 65,
      "Senior (65+)",
      "Non-senior",
      .label = "Senior citizen (age 65+)",
      .description = "age >= 65 coded as 'Senior (65+)'; everyone else as 'Non-senior'."
    )
  ) |>
  select(age, senior)
#> Error in dplyr::mutate(base_data, ..., .keep = .keep): ℹ In argument: `senior = if_else(...)`.
#> Caused by error in `if_else()`:
#> ! `...` must be empty.
#> ✖ Problematic arguments:
#> • .label = "Senior citizen (age 65+)"
#> • .description = "age >= 65 coded as 'Senior (65+)'; everyone else as
#>   'Non-senior'."

new@metadata@transformations
#> $dem
#> [1] "if_else(pid3 == 1, \"Democrat\", \"Non-Democrat\", missing = \"Unknown\")"
#>

Usage

Arguments

Value

See also

Examples