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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 Lithuania |
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1.2. Contact organisation unit | Living Standards and Employment Statistics Division |
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1.5. Contact mail address | 29 Gedimino Ave, Vilnius, Lithuania |
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2.1. Metadata last certified | 21/12/2022 | ||
2.2. Metadata last posted | 29/09/2023 | ||
2.3. Metadata last update | 29/09/2023 |
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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; in Lithuania it has been conducted since 2003. 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: Informacinių technologijų naudojimo namų ūkiuose tyrimas English: IT usage in households survey Questionnaire in national language and the translation in English are available in the annex. Annexes: Questionnaire in national language National questionnaire in English |
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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:
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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 | ||||||||||||
No deviations in scope. |
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3.4. Statistical concepts and definitions | ||||||||||||
The survey is collecting data of 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. Deviations from standard ICT concepts: No deviations. |
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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 | ||||||||||||
Entire country. |
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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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Last three months before the interview (approximately first quarter of the year); Last twelve months before the interview for e-government variables (approximately previous year). |
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5.1. Survey period | |||
21/03/2022 – 04/07/2022 |
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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: No complementary national legislation |
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6.2. Institutional Mandate - data sharing | |||
Not applicable |
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7.1. Confidentiality - policy | |||
In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees the confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of Statistics Lithuania. |
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7.2. Confidentiality - data treatment | |||
After the survey data is collected and the initial check and correction of the database is done, the data is depersonalised (names and addresses of the respondents are removed from the corrected database). Further steps (secondary editing, calculation of estimates, preparation for the transmission and dissemination) are performed with a depersonalized microdata base. |
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8.1. Release calendar | |||
Statistical information is published on the Official Statistics Portal osp.stat.gov.lt according to the approved Official Statistics Calendar. |
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8.2. Release calendar access | |||
The release calendar can be accessed on the Official Statistics Portal: Calendar.lt |
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8.3. Release policy - user access | |||
Statistical information is prepared and disseminated under the principle of impartiality and objectivity, i.e. in a systematic, reliable and unbiased manner, following professional and ethical standards (the European Statistics Code of Practice), and the policies and practices followed are transparent to users and survey respondents. All users have equal access to statistical information. All statistical information is published at the same time – at 9 a.m. on the day of publication of statistical information as indicated in the calendar on the Official Statistics Portal. Relevant statistical information is sent automatically to news subscribers. The President and Prime Minister of the Republic of Lithuania, their advisers, the Ministers of Finance, Economy and Innovation as well as Social Security and Labour or their authorized persons, as well as, in exceptional cases, external experts and researchers have the right to receive early statistical information. The specified persons are entitled to receive statistical reports on GDP, inflation, employment and unemployment and other particularly relevant statistical reports one day prior to the publication of this statistical information on the Official Statistics Portal. Before exercising the right of early receipt of statistical information, a person shall sign an undertaking not to disseminate the statistical information received before it has been officially published. Statistical information is published following the Official Statistics Dissemination Guidelines and Statistical Information Dissemination and Communication Rules of Statistics Lithuania approved by Order No DĮ-176 of 2 July 2021 of the Director General of Statistics Lithuania. |
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Annual |
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10.1. Dissemination format - News release | |||
News release can be accessed on the Official Statistics Portal: NewsRelease Annexes: News release 2022 |
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10.2. Dissemination format - Publications | |||
Information is published in the e-publication and can be accessed on the Official Statistics Portal Digital Economy and Society in Lithuania. |
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10.3. Dissemination format - online database | |||
Database of Indicators (Science and technology -> Information and communication technologies -> Information and communication technologies in households). |
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10.3.1. Data tables - consultations | |||
6 294 in the year 2021. |
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10.4. Dissemination format - microdata access | |||
Microdata are available and provided for scientific purposes according to the provisions set in the Description of Procedures for the Provision of Confidential Statistical Data for Scientific Purposes. More information is available on the Official Statistics Portal, at Data for scientific purposes. |
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10.5. Dissemination format - other | |||
Public data files: users are also provided with opportunity to access public files with statistical data on observation units. More information is available on the Official Statistics Portal, at Public data files. Statistical information can also be provided on user request (more information is available on the Official Statistics Portal). |
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10.5.1. Metadata - consultations | |||
Not available |
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10.6. Documentation on methodology | |||
Methodological documents are published on the Official Statistics Portal, section Information and communication technologies |
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10.6.1. Metadata completeness - rate | |||
97% |
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10.7. Quality management - documentation | |||
The quality of statistical information and its production process is ensured by the provisions of the European Statistics Code of Practice and ESS Quality Assurance Framework. In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. The main trends in activity of Statistics Lithuania aimed at quality management and continuous development in the institution are established in the Quality Policy. Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify the areas which need improvement and to promptly eliminate the shortcomings. More information on assurance of quality of statistical information and its preparation is published in the Quality Management section on the Statistics Lithuania website. |
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11.1. Quality assurance | |||
Since 2007 Statistics Lithuania operates a management system that complies with the requirements of the international quality management system standard ISO 9001. Quality assurance includes annual training courses for interviewers, Interviewer instructions (in national language). Statistical quality control at micro- and macrodata levels is performed. Statistical indicator estimates are compared with the previous period’s estimates. Since 2005, user opinion surveys have been conducted on a regular basis. Official Statistics Portal traffic is monitored, website visitor opinion polls, general opinion poll on the products and services of Statistics Lithuania, target user group opinion polls and other surveys are conducted. In 2007, the compilation of a user satisfaction index was launched. The said surveys are aimed at the assessment of the overall demand for and necessity of statistical information in general and specific statistical indicators in particular. |
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11.2. Quality management - assessment | |||
Data quality is in accordance with principles of accuracy and reliability, timeliness and punctuality, coherence and compatibility. The questionnaire was prepared and the survey was carried out according to the methodological recommendations of Eurostat. |
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12.1. Relevance - User Needs | |||
The main users of national data on the use of ICT by households and by individuals are national public institutions and authorities, non-governmental and international organisations, the media, politicians, business and research communities, students, pupils and others. Major share of the statistical information produced is used to set EU and national digital targets for 2030 and to measure their achievement through the Digital Economy and Society Index (DESI), which measures EU countries' progress and the European Digital Agenda. Need for additional indicators for planning and monitoring is presented by the Information Society Development Committee. |
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12.2. Relevance - User Satisfaction | |||
Close relationships with the main users of the survey information allow us to get a clear picture of the main users' satisfaction with the following aspects of quality: good accuracy and reliability of results, very good timeliness, satisfactory accessibility, good clarity and comparability over time, very good completeness and relevance. |
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12.3. Completeness | |||
All indicators and their components established by legislation are prepared. In 2022, Statistics Lithuania provided all mandatory and optional variables. |
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12.3.1. Data completeness - rate | |||
100% |
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13.1. Accuracy - overall | |||||||||||||||||||||||||||||||||
To achieve greater accuracy, non-sampling errors are reduced. The proposed model questionnaire was translated, adapted, tested by special working group for testing questionnaires and several respondents. Prepared questionnaire was legitimated by order of the Director General of Statistics Lithuania. The manual for interviewers was prepared. The sample of 6 000 individuals was selected. The Population Register was used as a sampling frame. Software for interviewing, including several validation rules to prevent coherence errors, ensuring immediate correction at the moment of interviewing, was prepared and tested. Electronic questionnaire was complemented with some methodological explanations, definitions and some other helpful information and prefilled with personal data from Population register and Social insurance board database. |
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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 . The estimation of the sampling variance should ideally take into account the sampling design (e.g. the stratification). More information on methodology for calculating precision estimates is detailed in the annexes below. Annexes: Calculation of the standard error: method, basic formula, main reference in the literature |
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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): 2 480 (estimated – 1 260 791) Estimated proportion (in %): 60.1 Standard error (in percentage points): 0.71 Details of the breakdowns are available in the Annexes. Annexes: SIMS_2022_annex with table 13.2.1 |
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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 | |||||||||||||||||||||||||||||||||
The sampling frame was made up using the Population Register. The register is updated regularly. The sampling frame was compiled 7 days prior to the fieldwork. The whole country is covered by the survey. ICT covers individuals aged 16-74 living in private households. Persons living in collective households and in institutions were excluded from the target population. The calibration of sampling weights using the known values of age, sex and urban/rural place of residence enables adjustment for the under coverage of the sampling frame. |
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13.3.1.1. Over-coverage - rate | |||||||||||||||||||||||||||||||||
Persons living in the collective households and in the institutions are accessible via the frame. The list of addresses of the institutions is consulted to prevent selection of the persons living in the institutions for the survey sample. There are nearly 12 thousand persons, i.e. about 0.6 % of target population. |
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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: Young people sometimes cannot indicate household income. 2) Questionnaire design and testing: Questionnaires are tested by special testing group to ensure that the issues are understood in the same way. The e-questionnaire provides explanations, definitions, examples and some other helpful information. 3) Interviewer training: In 2022 remote training of interviewers took place on 24 March. All interviewers participated, including Telephone Interview Centre interviewers, as well as supervisors (survey organisers) and specialists of the Survey Organisation Division. Brief information about the 2021 survey results with the comparison of the main results of other EU countries are presented. The 2022 survey questionnaire was displayed in the electronic survey system with all questions being discussed sequentially. The manual for the interviewers was provided, instructions and consultations were provided by phone and e-mail during the fieldwork. 4) Proxy interview rates: 0.98 % |
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13.3.3. Non response error | |||||||||||||||||||||||||||||||||
Information about non-respondents: not available |
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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
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13.3.3.1.1. Unit non-response – sample sizes | |||||||||||||||||||||||||||||||||
Comments, if any: |
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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: Weights used to reduce the impact of the rate of uneven non-participation in the survey in different strata on the survey results. In order to make the sample data proportionate to the population data, the weights of the sample plan were calibrated by group of the population in strata, age and sex. 2) Methods used for minimizing unit non-response: Advance letters accompanied by a leaflet with some statistics on ICT usage from the previous surveys were sent to the about 53% of the selected persons by e-mail on 21 March. To the others, whose e-mail addresses were not known in advance, letters by post were sent on 18 March. Postcard reminders were sent to the selected persons who had not filled questionnaire on 13 April. Reminders by e-mail were sent 4 times. If during the fieldwork selected person was not found for the first time interviewer must visit the selected address at least two more times. 3) Substitution permitted: Allowed only for persons not using the Internet. The share of proxy interviews – 0.98 per cent. (The share of persons who have never used the Internet – 11.9%). 4) Substitution rate (in %): 0.98% (0.4% visiting households, 0.6% answered by telephone). |
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13.3.3.2. Item non-response - rate | |||||||||||||||||||||||||||||||||
Items with low response rates (observed rates in %): item G18 Household income non response 23.6% of observations (22.6% weighted). |
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13.3.4. Processing error | |||||||||||||||||||||||||||||||||
In 2022, there were none. |
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13.3.5. Model assumption error | |||||||||||||||||||||||||||||||||
Not requested for ICT Survey |
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14.1. Timeliness | |||
19/08/2022 |
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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 | |||
33 calendar days |
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14.2.1. Punctuality - delivery and publication | |||
33 calendar days |
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15.1. Comparability - geographical | |||
Fully comparable between areas and satisfies the ESS/international concepts, definitions. |
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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: For the preparation of statistics for 2008–2012, population figures recalculated based on the 2011 Population and Housing Census data are used (released in the databases and publications for the year 2013). The break in the time series due to the recalculation of information in 2008 has only a negligible impact on data comparability over time. |
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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: The table in the annexes lists the questions that do not reflect the coverage of subjects and characteristics of Annex 2 of the Commission Delegated Regulation (EU) 2021/1898 of the 20 July 2021. Annexes: SIMS_2022_annex with Table 1(mandatory questions) |
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15.4.2. Survey questionnaire – optional questions | |||
Adoption of OPTIONAL questions and items in the Eurostat model questionnaire 2022: The table in the annexes 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. Annexes: SIMS_2022_annex with optional variables table |
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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: No deviations from Eurostat’s routing otherwise |
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Restricted from publication |
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17.1. Data revision - policy | |||
The revision policy applied by Statistics Lithuania is described in the Description of Procedure for Performance, Analysis and Publication of Revisions of Statistical Information. |
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17.2. Data revision - practice | |||
The final results are published, no scheduled revisions are performed. |
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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 | |||
IT usage in households survey is a stand-alone survey based on a voluntary participation of the selected persons. Sampling frame: Population Register was used for the survey sampling. This database includes data on the residents of the country: the citizens of Lithuania, the citizens of foreign countries or persons without citizenship, declaring the place of residence in Lithuania or registering any changes of the civil state in a registry office. Resident population statistics data (number of persons by sex, age groups and in strata) were used for weighting and grossing-up. The resident population and its structure are determined using a cohort-component method (based on the results of the most recent population and housing census, statistical data on live births, deaths, individuals changing their usual place of residence, territorial-administrative changes). Statistical data on live births, deaths, individuals changing their usual place of residence are received from the central database of the Population Register. Known shortcomings of the sampling frame: Not all movements of the population within the country are reflected, whereas not all persons report about changing the address to a respective institution, or the declared place of residence is not the main place of residence. Consequently, if the person included in the sample does not live at the address specified, the person actually living at that address whose birthday is the closest to the date of the interview is asked to answer the survey questionnaire. |
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18.1.2. Sampling design | |||
Sampling design: A one-stage stratified sample design with a simple random sample in strata was used. The size of the sample of persons in every stratum is proportional to the number of residents aged 16–74 in them. The entire Lithuanian territory was divided into 25 non-overlapping groups – strata. The population of the 5 largest cities of Lithuania, towns and rural areas of the 10 counties were divided into separate strata. One individual was interviewed in the selected address. |
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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: Combination of techniques was applied: self-accomplished survey via web based application (CAWI) combined with CATI and face-to-face interviews. 2) Short description of the survey method: Distribution of survey respondents by data collection technique: 15.9% – self-completed web interviews (CAWI), 16% – face-to-face interviews (CAPI), 68% – telephone interviews (CATI), 0.1% (5 cases) – paper assisted personal interview (PAPI). 3) Variables completed from an external source:
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18.4. Data validation | |||
Testing procedure: population coverage and non-response rate are checked, the results are compared with the previous year estimates. |
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18.5. Data compilation | |||
Data editing, missing value imputation, weight adjustment for non-response, calibration are performed. Data processing is done by SAS. The household income has missing values. The household member equalised income homogeneity groups were determined, and missing income simulated according to the normal distribution. Calibration of the design weights is done by SAS macro CLAN adjusting the set of respondents for non-response and to the demographic data in the groups selected, and calibrated weights are obtained. |
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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: The household income has missing values. The household member equalised income homogeneity groups were determined, and missing income simulated according to the normal distribution. Calibration of the design weights is done by SAS macro CLAN adjusting the set of respondents for non-response and to the demographic data in the groups selected, and calibrated weights are obtained. |
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18.5.3. Grossing-up procedures | |||
Grossing up procedures have been applied to: the same procedure was used for the households and for the individuals. Description of the weighting procedures: Sample weights were used to calculate estimates because population quantities were estimated using the sample. In this survey, parameters were estimated using calibrated weights. Statistics Lithuania used the number of persons in sex, age groups and in strata from demographic data as auxiliary information. Please consult the details in the annexes below. Annexes: Weighting procedures for households and individuals |
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18.6. Adjustment | |||
Not relevant |
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18.6.1. Seasonal adjustment | |||
Not relevant |
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Leaflet 2022 for respondents Metadata 2022 Methodology in Lithuanian language Interviewer instructions 2022 in Lithuanian language |