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Informatics & Methodology

Informatics & Methodology. The Transition from GEIS to Banff Chris Mohl, Yves Deguire, Rob Kozak, Chantal Marquis Statistics Canada. C anada. Statistics Statistique Canada Canada. Similarities of GEIS and Banff. Primarily for imputation of numeric data (non-negative)

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Informatics & Methodology

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  1. Informatics & Methodology The Transition from GEIS to Banff Chris Mohl, Yves Deguire, Rob Kozak, Chantal Marquis Statistics Canada Canada Statistics Statistique Canada Canada

  2. Similarities of GEIS and Banff • Primarily for imputation of numeric data (non-negative) • Modules for edit analysis, outlier detection, error localization and imputation • Fellegi-Holt rule of minimum change and Chernikova’s algorithm used to identify fields to be imputed • Edits must be expressed in linear form

  3. GEIS Oracle/SQL UNIX, mainframe Run modules in a specific order User must write code Banff SAS PC, UNIX, mainframe Decoupled modules (run in any order) User can write SAS code, use SAS wizards or Banff processor (SAS code generator) Differences of GEIS and Banff

  4. Methodological Enhancements in Banff • Estimation procedures can now handle negative data • Random error term can be added to imputation for all estimator functions • Additional options for outlier detection • More edit variables can be processed efficiently

  5. Future Enhancements to Banff Version 2 (autumn 2005) • Negative data allowed in all modules • SAS wizards available for use Future versions? • Allow non-linear edits via Logiplus software • Functionality to allow use of qualitative data • Generalize the Banff processor

  6. Demonstration of Banff Wednesday May 18 at 14:00 11th floor R.H. Coats Building

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