Skip to main content
en
English
Legal notice
Privacy policy
Cookies
Contact on Europa
Search on Europa
Search
⟶ Advanced search
CROS
Collaboration in Research and Methodology for Official Statistics
You are here
European Commission
»
Eurostat
»
CROS
»
ESSnet on quality of multisource statistics - KOMUSO
»
Quality Guidelines for Multisource Statistics - QGMSS
»
Quality Measures and Calculation Methods (QMCMs) including practical examples
»
qmcm_a_17
Log in (via EU Login)
A TO Z
Administrative data
Architecture
Big Data
Business statistics
Catalogues
Classification
Culture
Data analysis
Data collection
Data exchange
Data integration
Data provision
Data warehousing
Demographic and social statistics
Design
Disclosure control
Dissemination
Education
Energy
Estimation
GIS
Governance
Handbooks
Harmonisation
Health
Income and consumption
Indicators
Information models
Information society
Information Technology
International trade and balance of payments
Journals
Labour
Living conditions, poverty and cross-cutting social issues
Macroeconomic statistics
Metadata
Methodology
Microdata
Multisource statistics
Open Data
Quality
Regional and small area statistics
Registers
Research
Science and innovation
Seasonal adjustment
Security
Skills
Standardisation
Survey integration
Tourism
Validation
Visualisation
GROUPS
GENERAL INTEREST GROUPS
Data and Metadata exchange
Big data
COMmunicating Uncertainly in Key Official Statistics
European Master in Official Statistics (EMOS)
ENBES
EIGE Administrative Data Violence
ESS Architecture
ESS Standardisation
EURONA
EU-SILC scientific use files
Global city and settlement definition
Labour Market Areas
Linked Open Data Interest Community
Microdata Access
Research Projects under Framework Programmes
Research programme - Horizon 2020
Seasonal adjustment
Seasonal adjustment - JDemetra+ software
Social indicators: Flash estimates
Social indicators: Income, Consumption and Wealth
Social indicators: Labour skills
Survey integration
Trusted Smart Statistics – Web intelligence Hub
Web Intelligence for Measuring Emerging Economic Trends: the Drone Industry
Workshop Scanner Data Web Scraping
CENTRES OF EXCELLENCE
Centre of Excellence on Data Warehousing
Centre of Excellence on Seasonal Adjustment
Centre of Excellence on Statistical Disclosure Control
Centre of Excellence on Statistical Methods and Tools
ESSNET
ESSnet - generalities
ESSnet Linked Open Statistic
ESSnet Sharing common functionalities in ESS
ESSnet I on Big Data
ESSnet II on Big Data
ESSnet on quality of multisource statistics
ESSnet Implementing shared statistical services
Third EU-SILC Network on income and living conditions (NetSILC-3)
MEETS ESSnet
Annual Assessments
Meetings/workshops
Trusted Smart Statistics - Towards a European platform for Trusted Smart Surveys
Trusted Smart Statistics - Web Intelligence Network
ESS GOVERNANCE GROUPS
DIME / ITDG
Working Group on Methodology
Working Group on IT
Working Group on Quality
Working Group on Standards
Expert Group on IT Security
Expert Group on Seasonal Adjustment
Expert Group on Standardisation
Expert Group on Statistical Disclosure Control
TF on Validation
ESS VISION 2020
ESS Vision 2020 programme
ESS Vision 2020 ADMIN
ESS Vision 2020 DIGICOM
ESS Vision 2020 Information Models & Standards
ESS Vision 2020 Shared Services
ESS Vision 2020 Validation
EVENTS
UPCOMING EVENTS
Full event calendar
29/10/2023
: 9th SDMX Global Conference
04/06/2024
: European Conference on Quality in Official Statistics (Q2024)
PAST EVENTS
Full calendar of past events
15/07/2023
: 64th ISI World Statistics Congress
31/03/2023
: The first European Statistics Awards for Web Intelligence
06/03/2023
: Conference on New Techniques and Technologies for Statistics
02/03/2023
: EUROPEAN BIG DATA HACKATHON 2023
06/12/2022
: 10th International Conference on the Use of R in Official Statistics
CREATE AN EVENT
NEWS
NEWS
All CROS news
Call for abstracts for the Virtual European Establishment Statistics Workshop (EESW21)
Privacy in Statistical Databases 2020 (PSD 2020)
EU Open Data Days
Call for Papers for a special issue on “Respondent Burden” in the Journal of Official Statistics
10th European Conference on Quality in Statistics - Q2020 Budapest
IN FOCUS
ESS Vision 2020 ADMIN Helpdesk
ESS Data Warehousing Helpdesk
CREATE A NEWS ITEM
HELP
User support
What is CROS?
WIN Helpdesk
ESS Data Warehousing Helpdesk
Question forum for EU-SILC scientific use files
MY CROS
qmcm_a_17
Language:
English
qmcm_a_17.pdf
‹ example_qmcm_a_16
up
qmcm_a_18 ›
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
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 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
at_logo
cbs_logo
dk_logo
ir_logo
ir_logo_small
istat_logo
ksh_logo
lt_logo
ssb_logo
wordcloud
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
