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Check that outcome variables are within [0, 1]

Source: R/check_study_data.R
check_y_bounds.Rd

Summarises the min and max of each outcome variable and flags any that fall outside [0, 1].

Usage

check_y_bounds(
  data,
  study_id = NULL,
  outcomes = NULL,
  prefix = "Y_",
  exclude = NULL
)

Arguments

data

A data frame or tibble.

study_id

Optional character scalar. If provided, a study_id column is appended to the returned tibble.

outcomes

Columns to check. Supply unquoted names or tidyselect helpers (e.g., starts_with("outcome_")), or a character vector of column names. If omitted, all columns starting with prefix are used (excluding "_missing" and "_s" suffixes).

prefix

Character string. Prefix used to auto-select outcome columns when outcomes is omitted (default: "Y_").

exclude

Additional columns to drop from the selection. Supply unquoted names or tidyselect helpers (e.g., ends_with("_raw")), or a character vector of exact column names. Applied after outcomes is resolved. NULL (the default) means no additional exclusions.

Value

A tibble with columns variable, min, max, in_bounds, and optionally study_id. A column with no numeric values at all gets NA for all three, so that an absent outcome is not reported as an out-of-bounds one.

Details

When outcomes is omitted, all columns whose names start with prefix are selected, excluding any that end with "_missing" or "_s" (standardised versions). Supply outcomes to override this default, or exclude to drop additional columns from whatever was selected.

See also

Other per-study checks: check_attrition(), check_balance(), check_covariate_missingness(), check_missingness_nona(), check_smd()

Examples

dat <- data.frame(Y_support = c(0, 0.5, 1), Y_oppose = c(0, 1.2, 0.8))
check_y_bounds(dat)
#> # A tibble: 2 × 4
#>   variable    min   max in_bounds
#>   <chr>     <dbl> <dbl> <lgl>    
#> 1 Y_support     0   1   TRUE     
#> 2 Y_oppose      0   1.2 FALSE    
check_y_bounds(dat, study_id = "my_study")
#> # A tibble: 2 × 5
#>   variable    min   max in_bounds study_id
#>   <chr>     <dbl> <dbl> <lgl>     <chr>   
#> 1 Y_support     0   1   TRUE      my_study
#> 2 Y_oppose      0   1.2 FALSE     my_study
check_y_bounds(dat, outcomes = "Y_support")
#> # A tibble: 1 × 4
#>   variable    min   max in_bounds
#>   <chr>     <dbl> <dbl> <lgl>    
#> 1 Y_support     0     1 TRUE