| Document Title | ENG | Presentations | Number | |
|---|---|---|---|---|
| Preliminary Agenda | WP 1 | |||
| INF.1 | Information Notice 1 | |||
| INF.2 | Information Notice 2 | |||
| Paper template | DOC | |||
| LaTeX template | ZIP | |||
| Report | ||||
| Topic (iii): Software tools and international collaboration | ||||
| Discussant slides: introduction and discussion | ||||
| Towards a generic approach to validation: the ValiDat foundation project (ValiDat) | WP 2 | |||
| The ValiDat foundation project: survey on the different approaches to validation applied within the ESS (Germany) | WP 3 | |||
| Flash estimates for Short Term indicators - data cleaning with X12 Arima (Austria) | WP 4 | |||
| A formal typology of data validation functions (Netherlands) | WP 5 | |||
| Integrated data entry and validation system in HCSO (Hungary) | WP 6 | |||
| Usage of external software tools at SURS - experiences and lessons learned so far (Slovenia) | WP 7 | |||
| Editing and imputation in Household Based Surveys - case of Household Budget Survey in Bosnia and Herzegovina (Bosnia and Herzegovina) | WP 8 | |||
| Topic (ii): Managing and supporting changes related to editing and imputation | ||||
| Discussant slides: introduction | ||||
| Discussant slides: summary | ||||
| Discussant slides: discussion | ||||
| Redefining roles and responsibilities in a new harmonized statistical production process: opportunities and challenges (Canada) | WP 9 | |||
| Managing changes in the E&I strategy of the Italian SBS (Italy) | WP 10 | |||
|
Implementation of selective editing methods at Statistics Finland using innovative and efficient team work methods (Finland) |
WP 11 | |||
| Improvement of the quality of statistics by Mezo-validation (Hungary) | WP 12 | |||
| Data collection optimization - first attempt (Hungary) | WP 13 | |||
| Imputation at the National Agricultural Statistics Service (USA) | WP 14 | |||
| Getting commitment to a new editing strategy (New Zealand) | WP 15 | |||
| Managing and supporting changes related to editing and imputation in the United Kingdom (UK) | WP 16 | |||
| Topic (i): Selective editing and macro editing | ||||
| Discussant slides: introduction and discussion | ||||
| Selective editing of business investments by using administrative data as auxiliary information (Italy) | WP 17 | |||
| Output editing based on winsorization in the French SBS multisource system Esane (France) | WP 18 | |||
| Developing a theoretical framework for selective editing based on modelling and optimisation (Spain) | WP 19 | |||
| Changes in macro-editing and score functions for Dutch STS (Netherlands) | WP 20 | |||
| Model-based selective editing procedures for agricultural price indices (Italy) | WP 21 | |||
| Selective and macro-editing of a large business based administrative data set (USA) | WP 22 | |||
| Method for reviewing selective editing thresholds at ONS, RSI pilot study (UK) | WP 23 | |||
| Topic (vi): Report of the Task Team on a Generic Process Framework for Statistical Data Editing | ||||
| Generic Statistical Data Editing Models (version 0.5) | WP 24 | |||
| Topic (iv): Evaluation and feedback | ||||
| Discussant slides: introduction | ||||
| Discussant slides: discussion | ||||
| Editing Big Data: an holistic approach (Netherlands) | WP 25 | |||
| Editing process and its quality regarding design and production phases using process metadata and calculation modules (Finland) | WP 26 | |||
| Analysis of the data preparation process of the structural survey of the federal population census (Switzerland) | WP 27 | |||
| Editing and evaluation of statistics based on administrative microdata - example by Norway (Norway) | WP 28 | |||
| Evaluation of Census 2011 survey estimates (Germany) | WP 29 | |||
| Using the CURIOS algorithm to manage the prioritization of CAPI surveys (France) | WP 30 | |||
| Topic (v): Emerging methods and data revolution | ||||
| Discussant slides: introduction and discussion | ||||
| Let the data speak: Machine learning methods for data editing and imputation (New Zealand) | WP 31 | |||
| Estimation and editing for data from different sources. An approach based on latent class model. (Italy) | WP 32 | |||
| An assessment of the feasibility of editing and imputing administrative tax return data to provide a substitute for survey data (UK) | WP 33 | |||
| Multiple ratio imputation by the EMB algorithm (Japan) | WP 34 | |||
| New results on automatic editing using hard and soft edit rules (Netherlands) | WP 35 | |||
Work Session on Statistical Data Editing
14 - 16 September 2015
Budapest Hungary