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Match data columns against codebook variable definitions (rules only)

Source: R/data_check_helpers.R
match_column_labels.Rd

For each column in columns_df, find codebook variables whose normalised name matches, respecting experiment-group scoping. Resolves multiple definitions by haven priority, then rule-based label-equivalence (normalize_label); genuinely differing labels are flagged conflicting_definition. The LLM tiers (fuzzy matching, semantic merge) are applied separately by codebook_check when llm_use(TRUE).

Usage

match_column_labels(columns_df, codebook_vars_df)

Arguments

columns_df

data columns to label (needs paper_id, source_file, column_name; optional group/experiment_group)

codebook_vars_df

parsed codebook variables (from parse_codebook())

Value

a data.frame with one row per input column: paper_id, source_file, column_name, group, label, codebook_variable, label_source, label_status, label_method.

Examples

cb <- parse_codebook(file.path(demofile("repo"), "documentation",
                               "stroop_data_codebook.csv"))
cols <- data.frame(paper_id = "stroop_effect", source_file = "stroop_data.csv",
                   column_name = c("congruent", "incongruent"))
match_column_labels(cols, cb)[, c("column_name", "label")]
#>   column_name
#> 1   congruent
#> 2 incongruent
#>                                                                                      label
#> 1   Reaction time (in seconds) to name all words in the congruent block of the Stroop task
#> 2 Reaction time (in seconds) to name all words in the incongruent block of the Stroop task