Data Cleaning Center for Survey and Assessment Data

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Documentation for package ‘DCC’ version 1.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

dcc_apply_codebook	Apply a declarative codebook to a dataset
dcc_audit_log	Accessors for dcc_result objects
dcc_capabilities	Machine-readable DCC capability document
dcc_check	Check a strict DCC project without changing data
dcc_cleaned	Accessors for dcc_result objects
dcc_codebook_changes	The planned changes of a codebook preview
dcc_config	A cleaning configuration
dcc_data	The dcc_data container
dcc_detect	Run a rule set against data (Detect stage)
dcc_detect_chunked	Run record-local checks over a file in chunks
dcc_detect_encoding	Detect the character encoding of a text file
dcc_dictionary	Canonical variable dictionary
dcc_dispositions	Terminal dispositions of a cleaning result
dcc_doctor	Run every validator over a dataset and rule set
dcc_execute	Execute actions on detected findings (Execute stage)
dcc_export_log	Export an audit log for external auditors
dcc_findings	The dcc_findings table
dcc_help	Explain a DCC workflow code in Chinese or English
dcc_import	Strict canonical import
dcc_item_map	Master item map of a form-mapped dataset
dcc_l0_diagnose	Level-0 structural diagnostics
dcc_manifest	Build a reproducibility manifest for a cleaning run
dcc_mapping_findings	Mapping problems found while aligning forms
dcc_map_forms	Map multi-form responses onto the master item bank
dcc_missing_states	Canonical cell-level missing states
dcc_provenance	Provenance chain of a dcc_data object
dcc_read	Read a data file into a dcc_data object
dcc_read_config	Read an Excel cleaning-plan configuration
dcc_read_plan	Read a strict DCC Excel or JSON plan
dcc_read_report	Read report of a dcc_data object
dcc_reconcile	Reconcile findings against logged changes (closed loop)
dcc_report	Generate a cleaning report (Report stage)
dcc_report_machine	Render the machine report bundle
dcc_report_model	Build and validate the normalized report model
dcc_report_staff	Render the bilingual staff report
dcc_report_statistical	Render the statistical report bundle
dcc_rerun	Re-run a cleaning pipeline from its manifest and verify the output
dcc_result_summary	Create a structured AI summary of a DCC result
dcc_rules	Load a declarative rule set from a YAML file
dcc_run	Run a cleaning workflow with one command
dcc_run_files	Output files written by a run
dcc_schema	Published JSON Schema for a DCC object
dcc_score	Score responses against an answer key
dcc_template	Create the strict bilingual DCC Excel template
dcc_trace	Trace the cleaning history of a record or cell
dcc_unhandled	Findings left unhandled by execution
dcc_validate_config	Validate a cleaning configuration
dcc_validate_data	Validate data against a rule set before detection
dcc_validate_json	Validate DCC JSON and JSON Lines artifacts
dcc_validate_jsonl	Validate DCC JSON and JSON Lines artifacts
dcc_validate_plan	Validate a strict DCC project plan
dcc_validate_report_model	Build and validate the normalized report model
dcc_validate_rules	Validate a rule set before it is used
dcc_validation_errors	The failing issues of a validation report
dcc_write_config_template	Write a starter Excel cleaning-plan template
detect_missing_items	Detect excessive item nonresponse per respondent
detect_response_time	Detect implausibly fast or anomalous response times
detect_score_anomaly	Detect group-wise score anomalies
detect_straightlining	Detect straight-lining (longstring)
detect_trap_items	Detect failed trap (attention-check) items