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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | Statistics Denmark |
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1.2. Contact organisation unit | Science, Technology and Culture |
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1.5. Contact mail address | Statistics Denmark, Sejrøgade 11, DK-2100 Copenhagen Ø |
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2.1. Metadata last certified | 12/12/2022 | ||
2.2. Metadata last posted | 12/12/2022 | ||
2.3. Metadata last update | 12/12/2022 |
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3.1. Data description | ||||||||||||
The EU survey on the use of ICT in households and by individuals is an annual survey conducted since 2002. In Denmark, it has been conducted since 2001. In 2022, the survey collects data on the access to information and communication technologies (ICT), on the use of the internet, e-government, e-commerce, internet of things, as well as green ICT. |
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3.1.1. Survey name in national and English languages | ||||||||||||
National language: It-anvendelse i befolkningen 2022 English: ICT use by individuals 2022 Questionnaire(s) in national language(s) and the translation in English are available in the annex. Annexes: National questionnaire in English National questionnaire in Danish |
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3.2. Classification system | ||||||||||||
The following common concepts and definitions apply under the Integrated European Social Statistics (IESS):
Additional classifications used in the national questionnaire: None |
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3.3. Coverage - sector | ||||||||||||
The ICT survey in households and by individuals covers those households having at least one member in the age group 16 to 74 years old. Internet access of households refers to the percentage of households that have an internet access, so that anyone in the household could use the internet. |
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3.3.1. Differences in scope at national level | ||||||||||||
None |
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3.4. Statistical concepts and definitions | ||||||||||||
The survey is collecting data about internet users, individuals who have used the internet in the three months prior to the survey. Regular internet users are individuals who used the internet, on average, at least once a week in the three months prior to the survey. This annual survey is used to benchmark ICT-driven developments, both by following developments for core variables over time and by looking in greater depth at other aspects at a specific point in time. While the survey initially concentrated on access and connectivity issues, its scope has subsequently been extended to cover a variety of subjects (for example, the use of e-government and e-commerce) and socio-economic analysis (such as regional diversity, gender specificity, differences in age, education and the employment situation). The scope of the survey with respect to different technologies is also adapted so as to cover new product groups and means of delivering communication technologies to end-users. For more details on the methodology applicable in each survey year, please consult the Methodological Manual for the respective year on CIRCABC - Methodological Manual - Information society statistics (europa.eu). Deviations from standard ICT concepts: None |
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3.5. Statistical unit | ||||||||||||
Households and Individuals |
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3.6. Statistical population | ||||||||||||
In the ICT usage survey, the target population for the different statistical units is: - individuals: all individuals aged 16 to 74; - households: all (private) households with at least one member aged 16 to 74. Target population composed of households and/or individuals:
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3.6.1. Non-compulsory age groups | ||||||||||||
Non-compulsory age groups also included in the target population:
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3.6.2. Population not covered by the data collection | ||||||||||||
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3.7. Reference area | ||||||||||||
Denmark |
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3.8. Coverage - Time | ||||||||||||
Year 2022 |
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3.9. Base period | ||||||||||||
Not applicable |
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Percentages of ‘Households’ and Percentages of ‘Individuals’ |
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For most questions the reference period is the last three months before the interview. A few questions cover the 'last year' before the interview. Data collection was performed in the second quarter of 2022. |
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5.1. Survey period | |||
31. March 2022 - 4. August 2022 |
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6.1. Institutional Mandate - legal acts and other agreements | |||
The legal basis for the 2022 EU survey on the use of ICT in households and by individuals is the Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples (OJ L 261 I, 14.10.2019, p. 1), as implemented by the Commission Implementing Regulation (EU) 2021/1223 of 27 July 2021 specifying the technical items of the data set, establishing the technical formats for transmission of information and specifying the detailed arrangements and content of the quality reports on the organisation of a sample survey in the use of information and communication technologies domain for reference year 2022 pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council (OJ L 2269, 27.07.2021, pp. 1-45). Complementary national legislation constituting the legal basis for the survey on the use of ICT in households and by individuals: None. The survey is voluntary for participants in Denmark |
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6.2. Institutional Mandate - data sharing | |||
Micro data is not shared between agencies in the national statistical system. There is only one statistical office in Denmark. Micro data is not shared in any other ways than:
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7.1. Confidentiality - policy | |||
Statistics Denmark has extensive procedures and systems to protect the information on Danish citizens and enterprises in our systems, and staff focus on continuously ensuring maximum data security. Measures taken are aimed at two types of risks: external, e.g. hackers, and internal, i.e. from employees and from users with special permission to use data with us. Please consult the page on Information security and data confidentiality |
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7.2. Confidentiality - data treatment | |||
Please consult the documents on Data for researchers, access to micro data |
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8.1. Release calendar | |||
The publication date appears in the release calendar. The date is confirmed in the weeks before. |
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8.2. Release calendar access | |||
The Release Calendar can be accessed on the English website: https://www.dst.dk/en/Statistik/planlagte The access is public. |
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8.3. Release policy - user access | |||
Statistics are always published at 8:00 a.m. at the day announced in the release calendar. No one outside of Statistics Denmark can access the statistics before they are published. |
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Annual |
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10.1. Dissemination format - News release | |||
News release on 16 August 2022 announcing the update of the public tables and describing main results regarding the use of apps to fight food waste. Annexes: News release national Aug 2022 |
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10.2. Dissemination format - Publications | |||
Apart from one or several news releases a comprehensive yearly publication is released each year. The publication covers all modules of the survey. |
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10.3. Dissemination format - online database | |||
The dissemination data can be accessed free of charge in Statbank Denmark, where users can find, combine and save data, including graphics e.g. figures based on the data. Tables were updated in August 2022 with 2022 data. Tables are placed under the newly reorganized theme 'Culture and Leisure, Digital behaviour and cultural habits'. List of tables: - [BEBRIT07]: Purchase via internet - per cent of the population (16-74 years) by type, latest purchase and time |
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10.3.1. Data tables - consultations | |||
The number of data extractions from StatBank tables showing the results of ICT HH DK 2022 was close to 4,000 between August-December 2022. |
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10.4. Dissemination format - microdata access | |||
Data is disseminated in micro data form through Statistics Denmark's Research Services. To facilitate register-based research, Statistics Denmark gives user access to de-identified micro data, i.e. data on person, family, household, workplace or company level. Access is given as secure remote access to servers at Statistics Denmark from the users' own computer through the Internet. |
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10.5. Dissemination format - other | |||
Other means used to disseminate the data include press releases and analyses done by main national users, OECD, ITU and Eurostat. For an example to other means of dissemination please refer to Trust in public services (www.digst.dk/media/25753/final-tilliden-til-den-digitale-offentlige-sektor.pdf) |
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10.5.1. Metadata - consultations | |||
Metadata information collected in the statistical documentation for 2022 was published in August 2022. Since the publication date, over 100 consultations of metadata related to the ICT HH survey 2022 edition have been registered. |
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10.6. Documentation on methodology | |||
The publicly available national documentation (metadata) is based on SIMS and its content is very similar to the quality report delivered to Eurostat via the ESS Metadata Handler. |
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10.6.1. Metadata completeness - rate | |||
100 percent according to Statistic Denmark's requirements. |
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10.7. Quality management - documentation | |||
Results from the quality evaluation of products and selected processes are available in detail for each statistics and in summary reports for the Working Group on Quality. |
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11.1. Quality assurance | |||
Statistics Denmark follows the principles in the Code of Practice for European Statistics (CoP) and uses the Quality Assurance Framework of the European Statistical System (QAF) for the implementation of the principles. This involves continuous decentralized and central control of products and processes based on documentation following international standards. The central quality assurance function reports to the Working Group on Quality. Reports include suggestions for improvement that are assessed, decided and subsequently implemented. |
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11.2. Quality management - assessment | |||
The quality of the survey in general is appraised to be high. In 2022, the survey results are based on responses from 4,363 respondents aged 16-74 years. This number is almost double of the required sample size according to the precision requirement. The survey is based on simple random sample and therefore the results are subject to a sampling error. Accuracy and error calculations have been produced and are attached in section 13.2. Sampling error. |
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12.1. Relevance - User Needs | |||
The survey is used by academia, consultancies, students, researchers, counties and ministries. Furthermore it is the subject of considerable attention from the media. The survey can be used to cover developments in digitalisation. Finally, the survey is used in both Nordic and European collaboration. At European level, European Commission users (e.g. DG CONNECT, DG GROW) are the principal users of the data on ICT usage and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage. User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies. Statistical Denmark has an on-going dialogue with a variety of national users about the contents and usage of the survey. The Contact Committee for the Digital Society, whose members represent central national users is used as a framework for the dialogue. |
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12.2. Relevance - User Satisfaction | |||
Users are regularly consulted about the contents of the statistics. The numbers of hits (consultations) on the data tables and news releases is being monitored to assess the usefulness of the data. In general, these numbers are very high compared to the average number of consultations across all statistica. The number of articles, news releases covering results from the survey are also monitored and studied. The survey on ICT use by individuals is one of the most used statistics produced by Statistics Denmark. No formal user satisfactory survey is conducted. Nevertheless, main users from ministries and other organizations, as well as researchers and journalists, generally express satisfaction with the quality and relevance of the survey results. |
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12.3. Completeness | |||
All mandatory and option variables have been collected and transmitted apart from two variables:
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12.3.1. Data completeness - rate | |||
99 percent |
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13.1. Accuracy - overall | |||||||||||||||||||||||||||||||||
Overall accuracy is estimated to be high due to large sample size, representativity of the sample, quality of the frame and actions taken to reduce non-sampling errors. The survey is based on a simple randomly selected sample, and the results are therefore subject to statistical uncertainty. For the entire population's access to the internet, however, the uncertainty is limited, as the degree of coverage here is high. In general, the degree of coverage is rather high in Denmark where ICT use is more common than in other EU countries. The uncertainty reflects variations in the collected data in relation to the sample size. The number of completed answers in the sample exceeds the number of answers necessary according to the precision requirement. This further increases the overall accuracy of the survey. |
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13.2. Sampling error | |||||||||||||||||||||||||||||||||
The sampling error reflects the fact that only a particular sample was surveyed rather than the entire population. It is estimated by the standard error and can be expressed by the square root of the estimate of the sampling variance. Calculation of the variance estimation (sampling error) is done by using regression estimation where auxiliary variables are used in the estimation process. The estimation of the sampling variance takes into account the sampling design. In the regression estimator it is assumed that the study variable can be explained by J auxiliary variables, X1 to XJ, according to the linear regression model. The estimation method used for the random variation of an estimator due to sampling is Taylor linearization. Please see the document annexed below. References to literature in the methodology used:
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13.2.1. Sampling error - indicators | |||||||||||||||||||||||||||||||||
Precision estimates for the question "Individuals having ordered goods or services for private use over the internet in the last 12 months" (individuals who ticked 'Within the last 3 months' or 'Between 3 months and a year ago' in question D1 of the 2022 model questionnaire): Number of respondents (absolute value for ‘Yes’ answers): 3,862 Estimated proportion (in %): 88.25 Standard error (in percentage points): 0.52 Details of the breakdowns are available in the Annex below. Annexes: Standard errors and deviations from Eurostat model questionnaire |
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13.3. Non-sampling error | |||||||||||||||||||||||||||||||||
See more details on non-sampling error below. |
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13.3.1. Coverage error | |||||||||||||||||||||||||||||||||
Negligible divergence between the target population and the frame population is ensured by utilizing a high quality register as frame population and high participation in the survey. The register used is called Central Person Register CPR is updated daily and contains all individuals with a registered address in Denmark. All authorities with which the CPR is in contact have been allocated a four-ciphered code. The codes are used for registration such that the CPR serves as an index to the authorities responsible for registering basic data. The authorities responsible for basic data are also obliged to report administrative changes, e.g. amalgamation of parishes, counties, etc., directly to the CPR, such that the register of authorities is up-to-date. With the modernization of the CPR it was possible to update the system on-line in the local civil registration offices. Therefore the CPR is updated in real-time all year round, in other words: 365x24x7. |
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13.3.1.1. Over-coverage - rate | |||||||||||||||||||||||||||||||||
No over-coverage. |
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13.3.1.2. Common units - proportion | |||||||||||||||||||||||||||||||||
Not requested in the ICT survey. |
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13.3.2. Measurement error | |||||||||||||||||||||||||||||||||
1) Measurement errors: Built-in filters in both CATI and CAWI questionnaires ensure that respondents are only asked questions that are relevant based on their answers to the previous questions. This mechanism ensures consistency in the responses and minimizes measurement errors. E.g. a respondent who has answered 'No' to Internet use, will not get questions on Internet activities. All filters in the questionnaire have worked as intended. 2) Questionnaire design and testing: Extensive testing of the questionnaire both in CAWI and CATI versions has been performed to avoid possible errors and sources of uncertainty. No errors arising from multi-mode and/or multi-source data collection have been detected. There can be some measurement errors due to very long and sometimes complex questionnaires as respondents become less motivated to make an effort and answer as correctly as possible. Some questions can be difficult to answer due to having to rely on memory (e.g. items purchased in the past three months). To minimize this problem the number of additional national questions has been strongly reduced from previous years. Another source of error are questions which are relevant for a majority of EU member states but not for Denmark. E.g. question C1b) Downloading/printing official forms is not reflecting the current situation/technology used in Denmark, where download is not necessary any more. Many public services obtain information from citizens via apps without citizens having to download official forms. 3) Interviewer training: CATI interviewers have undergone a short training to ensure that they full understand the content of the questionnaire. 4) Proxy interview rates: No proxy interviews are conducted in Denmark for this survey. |
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13.3.3. Non response error | |||||||||||||||||||||||||||||||||
Information about non-respondents: Response rates are falling in general. Response rates are lower among young people and individuals with another ethnic background than Danish. The use of auxiliary register information in the estimation process attempts to remedy the bias caused by the substantial unit non-response, the cost of bias reduction being larger standard errors. |
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13.3.3.1. Unit non-response - rate | |||||||||||||||||||||||||||||||||
The unit response rate is the ratio of the number of in-scope respondents (= the number of achieved interviews or the net sample size to the number of eligible elements selected from the sampling frame). Unit non-response rate for
Note: Individuals who cannot be reached e.g. due to 'secret' telephone numbers, are included under eligible elements. |
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13.3.3.1.1. Unit non-response – sample sizes | |||||||||||||||||||||||||||||||||
Comments, if any: Individuals who cannot be reached e.g. due to 'secret' telephone numbers are included under eligible elements. |
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13.3.3.1.2. Unit non-response – methods, minimization and substitution | |||||||||||||||||||||||||||||||||
1) Methods used for dealing with unit non-response: Updated and high quality frame population, at least 6 contacts by e-mail and /or traditional mail and telephone 2) Methods used for minimizing unit non-response: Grossing up method (see description under chapter 18.) 3) Substitution permitted: No 4) Substitution rate (in %): 0 |
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13.3.3.2. Item non-response - rate | |||||||||||||||||||||||||||||||||
Items with low response rates (observed rates in %): Item non-response is not possible as respondents can only proceed with the interview if they have answered the previous question. Incomplete answers are not used to calculate the results. |
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13.3.4. Processing error | |||||||||||||||||||||||||||||||||
None known |
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13.3.5. Model assumption error | |||||||||||||||||||||||||||||||||
Not requested for ICT Survey |
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14.1. Timeliness | |||
56 days National publication of all results was on 16 August 2022. |
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14.1.1. Time lag - first result | |||
Restricted from publication | |||
14.1.2. Time lag - final result | |||
Restricted from publication | |||
14.2. Punctuality | |||
The results of the survey were delivered without delay in relation to the scheduled deadline. No time lag. |
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14.2.1. Punctuality - delivery and publication | |||
The results of the survey were published without delay in relation to the scheduled deadline. |
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15.1. Comparability - geographical | |||
The survey is harmonized with the EU model questionnaire, which is used in most member states. In Denmark special care is taken to ensure that the national version does not differ from the model questionnaire due to incorrect translation etc. There is no problems of comparability between regions within Denmark, the same questionnaire, language and method is used, and the sample is representative. |
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15.1.1. Asymmetry for mirror flow statistics - coefficient | |||
Not relevant |
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15.2. Comparability - over time | |||
Possible limitations in the use of data for comparisons over time: The survey has been carried out since January 2001. A large part of the indicators have been replaced with others to be able to measure the newest trends in ICT. Key figures are comparable over time. The survey replaces the survey Personal computers and access to the Internet (Pc'ere og adgang til internet), carried out from May 1997 to the end of 2000. There have not been any changes in methodology that may have an impact on the comparability over time of the results delivered to Eurostat. The survey type, the reference sampling frame, scope and grossing-up method have been the same for a high number of years. A large share of indicators is not collected annually and are only available every second or third year. This is in line with the EU Model questionnaire and the regulation addressing the survey. |
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15.2.1. Length of comparable time series | |||
The length of comparable time series depends on the module and variable considered within each of the modules of the survey. |
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15.3. Coherence - cross domain | |||
Not applicable |
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15.3.1. Coherence - sub annual and annual statistics | |||
Not applicable |
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15.3.2. Coherence - National Accounts | |||
Not applicable |
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15.4. Coherence - internal | |||
All statistics are coherent within the dataset. |
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15.4.1. Survey questionnaire – mandatory questions | |||
MANDATORY questions in the Eurostat model questionnaire 2022: Please refer to the table describing standard errors and deviations from the model questionnaire annexed to 13.2.1. |
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15.4.2. Survey questionnaire – optional questions | |||
Adoption of OPTIONAL questions and items in the Eurostat model questionnaire 2022: Please refer to the table describing standard errors and deviations from the model questionnaire annexed to 13.2.1. The table lists the optional questions from the annual Eurostat model questionnaire 2022 included in the national questionnaire and their coverage for age groups beyond the standard scope. |
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15.4.3. Survey questionnaire – additional questions at national level | |||
Additional questions introduced in the national questionnaire:
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15.4.4. Survey questionnaire – deviations | |||
Effects of deviations from the routing used in the Eurostat model questionnaire: None. The structure of the national and the model questionnaire are the same. Only few national answer options are added regarding internet activities. |
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Restricted from publication |
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17.1. Data revision - policy | |||
No data revision. Only final indicators are published. |
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17.2. Data revision - practice | |||
Only final indicators are published. |
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17.2.1. Data revision - average size | |||
Not relevant |
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18.1. Source data | |||
The source of the raw data is described with more details in the paragraphs below. |
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18.1.1. Sampling frame | |||
The survey's population covers individuals between 16 and 74 years resident in Denmark (excluding Greenland and the Faeroe Islands), according to the register named The Central Register of Persons (Det Centrale Personregister, CPR). The sampling frame is Statistics Denmark’s population register, CPR, which is updated daily. This register (CPR) contains all individuals with a registered address in Denmark. The register covers birth date, sex, address, and family relations. The CPR is updated several times a day. The survey is a stand-alone voluntary survey. |
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18.1.2. Sampling design | |||
The sampling unit at first stage is Individuals. No self-representing PSU’s are included, the sample is a one stage simple random sampling. The sampling units are individuals in the CPR register aged 16-74 years. |
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18.1.3. Net effective sample size | |||
Restricted from publication | |||
18.2. Frequency of data collection | |||
Annual |
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18.3. Data collection | |||
1) Methods used to gather data: CATI and CAWI combined mode 2) Short description of the survey method: CATI and CAWI combined data collection method is used to reduce response burden and increase response rates. Initial contact by e-mail in eBoks, the mail box all citizens 15+ years are obliged to use. At least 5 and maximum 7 re-contacts by e-mail, paper mail or phone. This time consuming practice ensures improved representativity, quality data with lower unit non-response rates and standard errors. Both CAWI and CATI is programmed with built-in filters in accordance with routing structure in model questionnaire (MQ). All filters in the MQ are automatically taken into account. Extensive testing ensures that data is collected according to specifications laid down in the regulation. The proportion of answers collected by CATI is 20%. The rest (80%) is collected with CAWI. 3) Variables completed from an external source: Auxiliary variables are collected from registers. Since Denmark has well updated registers covering the requested background variables, register data is often used instead of direct response. Register data is available on all required breakdowns apart from contract work and perceived health. For the 2022 survey the following auxiliary variables were used: 'Income', 'Education level', 'Family structure', 'Marital status', 'Geographical data', 'Country of origin', 'Citizenship' and 'Occupation'. |
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18.4. Data validation | |||
The design and extensive testing of the CATI and CAWI questionnaires (built-in checks) minimizes routing errors and makes it impossible to complete an answer without answering all questions. Year to year checks are applied to monitor the answers. No answer is corrected or imputed. Micro data is undergone Eurostat data validation standards (no validation errors on 22 September 2022). |
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18.5. Data compilation | |||
The grossing up procedure utilizes background variables and provides some adjustment for non-response. There is no imputation. Information on background variables is merged with answers with the help of a unique ID (CPR number) that is both available in the frame population and in the various registers. |
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18.5.1. Imputation - rate | |||
For the target indicator "Individuals having ordered goods or services for private use over the internet in the last 12 months" (individuals who ticked 'Within the last 3 months' or 'Between 3 months and a year ago' in question D1 of the 2022 model questionnaire): Imputation rate (% of observations): 0 Imputation rate (share of estimate): 0 |
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18.5.2. Use of imputation methods | |||
Methods used to impute item non-response: None applied |
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18.5.3. Grossing-up procedures | |||
Grossing up procedures have been applied to: both Individuals and Households with the help of two different weights. Description of the weighting procedures: The weighting and subsequent estimation of standard error - based on Taylor linearization - is done using the software package CLAN, a collection of SAS macros developed by Statistics Sweden. CLAN utilizes correlation between auxiliary and study (ICT) variables in the regression estimation. Denmark has well updated and extensive registers providing accurate and reliable data on each citizen. The final weights are determined using calibration estimation. Weighting aligns the response data to the frame totals grouped in a number of demographic, income and social register variables:
The use of auxiliary register information in the estimation process attempts to remedy the bias caused by unit non-response; the cost of bias reduction is slightly larger standard errors. The results of the survey are grossed-up to ensure their representativeness. After collecting the data, the sample is grouped by a number of background variables, such as age and gender. Each answer gets a 'weight' that corrects possible biases. The calculations are done by a regression estimator. Annexes: Explanation of grossing up method |
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18.6. Adjustment | |||
Not relevant |
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18.6.1. Seasonal adjustment | |||
Not relevant |
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