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Collaboration in Research and Methodology for Official Statistics
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ESSnet on quality of multisource statistics - KOMUSO
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Workshop on Quality of Multisource Statistics
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Invitation letter
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Invitation letter
Document date:
Monday, 23 May, 2016
Language:
English
invitation_workshop_budapest.pdf
‹ Invitation - annex
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ESSnet on quality of multisource statistics - KOMUSO
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
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example_qmcm_a_4
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example_qmcm_a_5
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example_qmcm_a_6
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example_qmcm_a_7
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qmcm_a_11
example_qmcm_a_11
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example_qmcm_a_12
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qmcm_a_14
example_qmcm_a_14
qmcm_a_15
example_qmcm_a_15
qmcm_a_16
example_qmcm_a_16
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qmcm_a_18
example_qmcm_a_18
qmcm_a_19
example_qmcm_a_19
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example_qmcm_a_20
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example_qmcm_a_21
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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
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Quality Guidelines for Frames in Social Statistics - QGFSS
KOMUSO workshop December 6th and 7th - material
Quality Guidelines for Multisource statistics (QGMSS) version 0.81 - workshop reference
Workshop program and material including questions for preparation
SGA (Specific Grant Agreement) 1
Workplan of KOMUSO project
Description of task in KOMUSO project, SGA1
WP1 - Checklists for evaluating the quality of input data
Final report of WP 1 (KOMUSO)
Overview of methods
WP2 - Methodology for the assessment of the quality of frames for social statistics
WP2 final report (KOMUSO)
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
Evaluating the Quality of Administrative Data as Input for Official Statistics - paper
Workshop photo
Workshop on Quality of Multisource Statistics
Documents
Agenda of the Budapest workshop
Invitation - annex
Invitation letter
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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 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
WP4 - Communication Plan
SGA (Specific Grant Agreement) 3
Business case of the ESSnet on quality of multisource statistics
