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Compute Trace Levels for ADaM Variables

Source: R/trace_levels.R
compute_trace_levels.Rd

Assigns a traceability level (L0–L3) to each ADaM variable in the trace model based on available mapping, derivation text, and confidence scores.

Usage

compute_trace_levels(trace_model)

Arguments

trace_model

A trace_model object from build_trace_model().

Value

A tibble with columns: adam_dataset, adam_var, trace_level, has_mapping, has_derivation_text, n_candidates, max_confidence.

Details

Trace levels:

  • L0: No mapping and no derivation text.

  • L1: Derivation text present but no SDTM mapping.

  • L2: Mapping to SDTM variable/domain exists.

  • L3: Mapping exists AND (confidence >= threshold OR derivation text present alongside mapping).

Examples

adam_meta <- data.frame(
  dataset = "ADSL", variable = c("STUDYID", "USUBJID", "AGE", "AGEGR1"),
  label = c("Study ID", "Unique Subject ID", "Age", "Age Group")
)
sdtm_meta <- data.frame(
  dataset = "DM", variable = c("STUDYID", "USUBJID", "AGE"),
  label = c("Study ID", "Unique Subject ID", "Age")
)
map <- data.frame(
  adam_dataset = "ADSL", adam_var = c("STUDYID", "USUBJID", "AGE"),
  sdtm_domain = "DM",   sdtm_var = c("STUDYID", "USUBJID", "AGE"),
  confidence = c(1.0, 1.0, 0.9)
)
tm <- build_trace_model(adam_meta, sdtm_meta, mapping = map)
compute_trace_levels(tm)
#> # A tibble: 4 × 7
#>   adam_dataset adam_var trace_level has_mapping has_derivation_text n_candidates
#>   <chr>        <chr>          <int> <lgl>       <lgl>                      <int>
#> 1 ADSL         STUDYID            3 TRUE        TRUE                           1
#> 2 ADSL         USUBJID            3 TRUE        TRUE                           1
#> 3 ADSL         AGE                3 TRUE        TRUE                           1
#> 4 ADSL         AGEGR1             1 FALSE       TRUE                           0
#> # ℹ 1 more variable: max_confidence <dbl>