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Stress Test a User-Supplied Measure

Source: R/measure.R
onet_measure_sensitivity.Rd

Runs the same user-supplied measure through alternative weight panels, bridges, and task-handling choices. The package does not create the substantive measure. It only changes the plumbing around that measure.

Usage

onet_measure_sensitivity(
  measure,
  weight_panels,
  bridges = list(no_bridge = NULL),
  task_ratings = NULL,
  task_metadata = NULL,
  include_supplemental = FALSE,
  weight_scale = "RT",
  year = NULL,
  cell = NULL,
  baseline = NULL
)

Arguments

measure

An onet_measure object.

weight_panels

A weight-panel data frame or named list of weight-panel data frames.

bridges

Optional bridge data frame, NULL, or named list of bridges.

task_ratings

For task-level measures, a task-ratings data frame or named list of task-ratings data frames.

task_metadata

Optional task metadata data frame or named list matching task_ratings.

include_supplemental

Logical vector. For task-level measures, controls whether Supplemental tasks are included.

weight_scale

Character vector of task rating scale ids. Defaults to "RT", the Task Ratings scale for Relevance of Task.

year

Optional single year passed to onet_measure_aggregate().

cell

Optional cell filter passed to onet_measure_aggregate().

baseline

Optional scenario label used as the movement baseline.

Value

A tibble with one row per scenario, aggregate results, movement fields, and provenance list-column metadata.

Examples

scores <- tibble::tibble(
  onet_soc_code = c("15-1252.00", "29-1141.00"),
  score = c(0.7, 0.2)
)
measure <- onet_measure(scores, "onet_soc_code", "score")
weights <- tibble::tibble(
  reference_soc_code = c("15-1252", "29-1141"),
  year = 2024L,
  employment = c(100, 300),
  weight_share = c(0.25, 0.75),
  source = "fixture",
  source_taxonomy = "2018 SOC",
  reference_taxonomy = "2018 SOC"
)
onet_measure_sensitivity(measure, weights)
#> # A tibble: 1 × 20
#>   scenario  measure_id task_release soc_vintage weight_panel bridge weight_scale
#>   <chr>     <chr>      <chr>        <chr>       <chr>        <chr>  <chr>       
#> 1 measure_… user_meas… NA           NA          weights      no_br… NA          
#> # ℹ 13 more variables: include_supplemental <lgl>, aggregate <dbl>,
#> #   total_employment <dbl>, covered_employment <dbl>,
#> #   employment_coverage_share <dbl>, n_occupations <int>,
#> #   n_reference_soc <int>, coverage <list>, provenance <list>,
#> #   baseline_scenario <chr>, baseline_aggregate <dbl>, movement <dbl>,
#> #   movement_percent <dbl>