### KOMUSO WP3 Literature reviews

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CROS

Collaboration in Research and Methodology for Official Statistics

- LR0_1 Quality Assessment Tool for Administrative Data
- LR1_1 Effect of classification errors on domain level estimates in business statistics
- LR2_1 Estimating classification errors in administrative and survey variables by latent class analysis
- LR2_2 Quality Assessment for Register-based Statistics - Results for the Austrian Census 2011
- LR2_3 Quality Assessment of Imputations in Administrative Data
- LR2_4 A Comparison of Methodologies for Classification of Administrative Records - Quality for Census Enumeration
- LR2_5 Effect of classification errors on domain level estimates in business statistics
- LR2_6 Effect of linkage errors using 1-1 linkage on inferences from the linked data
- LR2_7 Estimating measurement errors in administrative and survey variables by structural equation models
- LR2_8 Quality assessment of register-based census employment status
- LR2_9 Topics of statistical theory for register-based statistics and data integration
- LR3_1 Capture-recapture method and log-linear models to estimate register undercoverage
- LR3_2 Domain estimates of the population size
- LR4_1 Effect of reconciliation on estimated tables
- LR4_2 Constructing confidence images based on multiple sources
- LR5_1 Effect of reconciliation on estimated totals
- LR5_2 Effect of reconciliation on estimated totals
- LR5_3 Area-level small area estimation methods for domain statistics
- LR5_4 Automatic balancing using the “SCM method” with application to e.g. national accounts
- LR6_1 Macro Integration: Data Reconciliation

- LR0_1 Quality Assessment Tool for Administrative Data
- LR1_1 Effect of classification errors on domain level estimates in business statistics
- LR2_1 Estimating classification errors in administrative and survey variables by latent class analysis
- LR2_2 Quality Assessment for Register-based Statistics - Results for the Austrian Census 2011
- LR2_3 Quality Assessment of Imputations in Administrative Data
- LR2_4 A Comparison of Methodologies for Classification of Administrative Records - Quality for Census Enumeration
- LR2_5 Effect of classification errors on domain level estimates in business statistics
- LR2_6 Effect of linkage errors using 1-1 linkage on inferences from the linked data
- LR2_7 Estimating measurement errors in administrative and survey variables by structural equation models
- LR2_8 Quality assessment of register-based census employment status
- LR2_9 Topics of statistical theory for register-based statistics and data integration
- LR3_1 Capture-recapture method and log-linear models to estimate register undercoverage
- LR3_2 Domain estimates of the population size
- LR4_1 Effect of reconciliation on estimated tables
- LR4_2 Constructing confidence images based on multiple sources
- LR5_1 Effect of reconciliation on estimated totals
- LR5_2 Effect of reconciliation on estimated totals
- LR5_3 Area-level small area estimation methods for domain statistics
- LR5_4 Automatic balancing using the “SCM method” with application to e.g. national accounts
- LR6_1 Macro Integration: Data Reconciliation

- Quality Guidelines for Multisource Statistics - QGMSS
- Quality Measures and Calculation Methods (QMCMs) including practical examples
- qmcm_a_1
- example_qmcm_a_1
- qmcm_a_2
- qmcm_a_3
- example_qmcm_a_3
- qmcm_a_4
- example_qmcm_a_4
- qmcm_a_5
- example_qmcm_a_5
- qmcm_a_6
- example_qmcm_a_6
- qmcm_a_7
- example_qmcm_a_7
- qmcm_a_8
- example_qmcm_a_8
- qmcm_a_9
- example_qmcm_a_9
- qmcm_a_10
- example_qmcm_a_10
- qmcm_a_11
- example_qmcm_a_11
- qmcm_a_12
- example_qmcm_a_12
- qmcm_a_13
- qmcm_a_14
- example_qmcm_a_14
- qmcm_a_15
- example_qmcm_a_15
- qmcm_a_16
- example_qmcm_a_16
- qmcm_a_17
- qmcm_a_18
- example_qmcm_a_18
- qmcm_a_19
- example_qmcm_a_19
- qmcm_a_20
- example_qmcm_a_20
- qmcm_a_21
- example_qmcm_a_21
- qmcm_a_22
- qmcm_a_23
- qmcm_a_24
- example_qmcm_a_24
- qmcm_c_1
- example_qmcm_c_1
- qmcm_c_2
- qmcm_c_3
- qmcm_c_4
- example_qmcm_c_4
- qmcm_c_5
- example_qmcm_c_5
- qmcm_c_6
- example_qmcm_c_6
- qmcm_rv_1
- qmcm_t_1
- lr0_1
- lr2_4
- st2_1
- st2_7
- st_c_4

- Quality Measures and Calculation Methods (QMCMs) including practical examples
- Quality Guidelines for Frames in Social Statistics - QGFSS
- KOMUSO workshop December 6th and 7th - material
- SGA (Specific Grant Agreement) 1
- Workplan of KOMUSO project
- WP1 - Checklists for evaluating the quality of input data
- WP2 - Methodology for the assessment of the quality of frames for social statistics
- WP3 - Framework for the quality evaluation of statistical output based on multiple sources
- Discussion paper (WP3 KOMUSO)
- Final report of Work Package 3 (KOMUSO)
- KOMUSO WP3 Literature reviews
- LR0_1 Quality Assessment Tool for Administrative Data
- LR1_1 Effect of classification errors on domain level estimates in business statistics
- LR2_1 Estimating classification errors in administrative and survey variables by latent class analysis
- LR2_2 Quality Assessment for Register-based Statistics - Results for the Austrian Census 2011
- LR2_3 Quality Assessment of Imputations in Administrative Data
- LR2_4 A Comparison of Methodologies for Classification of Administrative Records - Quality for Census Enumeration
- LR2_5 Effect of classification errors on domain level estimates in business statistics
- LR2_6 Effect of linkage errors using 1-1 linkage on inferences from the linked data
- LR2_7 Estimating measurement errors in administrative and survey variables by structural equation models
- LR2_8 Quality assessment of register-based census employment status
- LR2_9 Topics of statistical theory for register-based statistics and data integration
- LR3_1 Capture-recapture method and log-linear models to estimate register undercoverage
- LR3_2 Domain estimates of the population size
- LR4_1 Effect of reconciliation on estimated tables
- LR4_2 Constructing confidence images based on multiple sources
- LR5_1 Effect of reconciliation on estimated totals
- LR5_2 Effect of reconciliation on estimated totals
- LR5_3 Area-level small area estimation methods for domain statistics
- LR5_4 Automatic balancing using the “SCM method” with application to e.g. national accounts
- LR6_1 Macro Integration: Data Reconciliation

- KOMUSO WP3 Suitability tests
- ST1_1 Suitability Test of Employment Rate for Employees (Wage Labour Force) (ERWLF)
- ST1_2 Analytical expressions for the accuracy of growth rates as affected by classification errors
- ST2_1 Overlapping numerical variables without a benchmark: Integration of administrative sources and survey data through Hidden Markov Models for the production of labour statistics
- ST2_2 Overlapping numerical variables with a benchmark
- ST2_3 Misclassification in several administrative sources
- ST2_4 Effect of the under-coverage of the classification variable on the domain estimates of the total in social statistics
- ST2_5 Effect of the frame under-coverage / over-coverage on the estimator of total and its Accuracy measures in the business statistics
- ST2_6 Effect of stratum changes, joining and splitting of the enterprises on the estimator of a total
- ST2_7 Output Quality for statistics based on several administrative sources
- ST45_1 Uncertainty measures for economic accounts

- WP4 - Communication, dissemination and implementation
- Abstract of NTTS2017 presentation by Zhang
- Abstract of NTTS2017 presentation by de Waal et al.
- Final report of WP4 (KOMUSO)
- Information for the Big Data society in official statistics
- NTTS2017 presentation by Li-Chun Zang
- NTTS2017 presentation by Ton de Waal
- Presentation of KOMUSO at CESS2016 conference
- Presentation of the ESSnet at CESS 2016 in Budapest
- Presentation of the ESSnet at Q2016 conference in Madrid
- Workshop photo
- Workshop on Quality of Multisource Statistics
- Documents
- Report of the workshop on quality of multisource statistics
- Workshop presentations and handouts
- Assuring statistical quality of Administrative data
- Development of a tool for quality assurance of administrative data
- ESSnet on Quality of multisource statistics
- Example of Slovenia: use of administrative data sources in statistical surveys
- Handout for discussion on questions related to WP2
- Komuso Work Package 3
- Possibilities to use administrative data sources for register based Census in Latvia
- Presentation of the ESS.VIP ADMIN
- Questions discussed in small groups
- The Challenges in compiling an Education Register in Iceland from multiple sources
- The Integrated production of Population Statistics in Finland
- Use of administrative data in Polish agriculture statistics
- WP2-frame quality
- Work Package 1:Checklists for evaluating the quality of input data

- SGA (Specific Grant Agreement) 2
- Work Package 1 - Guidelines on the quality of multisource statistics
- D1 - Outline of the quality guidelines document
- D2 - Sample section of the quality guidelines
- D3 - Action plan for SGA3 on Guidelines on the quality of multisource statistics
- D4 - First Draft "Quality Guidelines for Multisource Statistics (QGMSS)"
- D5 - Draft “Quality Guidelines for Multisource Statistics (QGMSS”) revised after comments from ESS relevant groups

- Work Package 2 - Quality guidelines for frames in social statistics
- Work Package 3 - Quality measures and indicators
- Examples of Quality Measures and Computation Methods (QMCMs)
- Intermediate report WP 3 "Quality measures and indicators" (2017.12)
- Quality Measures and Computation Methods (QMCMs)
- Revised draft of the Annex Version 2018-09-30
- WP3 Literature Review: Coherence in Multi-Source Statistics
- Work Package 3 - intermediate report 2018.06
- Work Package 3 Quality measures and indicators

- Work Package 4 - Communication plan

- Work Package 1 - Guidelines on the quality of multisource statistics
- SGA (Specific Grant Agreement) 3
- Business case of the ESSnet on quality of multisource statistics