Getting Started#

This guide helps you get up and running with ACRO for statistical disclosure control.

What is ACRO?#

ACRO (Automatic Checking of Research Outputs) is a Python package that provides statistical disclosure control for research outputs. It acts as a wrapper around common analysis functions, automatically checking for potential privacy disclosures.

Key Concepts#

Statistical Disclosure Control (SDC)#

SDC is the process of protecting confidential information in statistical data releases. ACRO implements principles-based SDC that:

  • Identifies potentially disclosive outputs

  • Applies mitigation strategies when needed

  • Maintains detailed audit trails

  • Supports human checker workflows

Disclosure Types#

ACRO checks for several types of disclosure:

  • Identity disclosure - When individuals can be identified

  • Attribute disclosure - When sensitive attributes can be inferred

  • Inferential disclosure - When statistical inference reveals information

Safety Thresholds#

ACRO uses configurable thresholds to determine safety:

  • Minimum cell count - Default: 10 observations

  • P-ratio threshold - Default: 0.1 for dominance

  • NK-rule - Default: n=2, k=85% for concentration

Basic Workflow#

  1. Initialize ACRO session

  2. Run analysis with ACRO methods

  3. Review disclosure warnings

  4. Finalize outputs for checking

Installation Requirements#

  • Python 3.10 or higher

  • pandas >= 1.5.0

  • statsmodels >= 0.13.0

  • PyYAML for configuration

Next Steps#