Description: We consider model-based optimal sampling designs for multipurpose surveys with multiple measures of size. The problem is motivated by surveys conducted by the United States Department of Agriculture’s National Agricultural Statistics Service (NASS), in which estimates of planted and harvested acres of different crops are of interest, and historical acreages are available on the frame as measures of size. We use convex optimisation to find the inclusion probabilities that minimise expected sample size subject to target precision requirements for different study variables, along with other inequality constraints. The precision requirements are computed as anticipated coefficients of variation under models relating study variables to frame measures of size. These same models are used in established NASS strategies for the multipurpose survey problem to obtain Multivariate Probability Proportional to Size (MPPS) inclusion probabilities. MPPS uses the measures of size to determine optimal inclusion probabilities for each model, then maximises over models. This solution is practical but not optimal. We compare the use of the MPPS and optimal inclusion probabilities under different designs (Poisson sampling and balanced sampling) and different estimators (calibrated and uncalibrated) via a Monte Carlo experiment using a simulated population of farms with realistic size and complexity.
Description: The United States Department of Agriculture’s (USDA) National Agricultural Statistics Service (NASS) produces more than 500 state and national reports a year and conducts a census of the nation’s 2.0 million farmers once every five years. At the heart of the Agency’s current data collection strategy is its ability to persuade a respondent to voluntarily respond to surveys. Respondents are becoming less willing to participate in surveys and demands for statistics and secure data access are becoming increasingly challenging. The gold standard to produce official statistics has been probability-based sample surveys for many years. Yet, the environment for obtaining information and providing statistical summaries to policy makers and the public is changing. At the same time, new technology and data sources provide opportunities to reduce the burden on the public by reducing the number of survey questions or even eliminating surveys while increasing timeliness, geographic or subpopulation detail, and statistical efficiency. This webinar will present practical approaches and techniques to data collection and provide examples of how technological advances and new procedures like the use of administrative and previously reported data can be used to enhance the experience for data providers and data users. This presentation will also share how the USDA-NASS plans to improve accessibility, ease of use, and access to data through modernizing data collection and product design.
Description: This webinar was jointly organized by the Inter-Secretariat Working Group on Household Surveys (ISWGHS) and the Global Network of Data Officers and Statisticians. We welcomed Marcelo Pitta, Thiago Meireles, and Pedro Silva from the Brazilian Network Information Center (NIC.Br) and the Brazilian Institute for Geography and Statistics (IBGE) who presented on the topic of leveraging non-probability samples and organic data for producing public statistics. The use of non-probability samples and of non-designed organic data for producing reliable public statistics is now a hot field of study and academic production. Such alternative data sources have been growing in importance due to the increasing demand for more timely and disaggregated data, resource constraints, and the increasing non-response associated with conventional probability sample surveys. Substantial body of emerging literature aims to enable official and public statistics producers to cope with the challenges presented by using such alternative data sources, namely the potential biases created by selection effects or undercoverage. The COVID-19 pandemic has compounded this scenario and increased the difficulties already faced by statistics producers. In this context, some experiments were developed to produce public data from alternative data sources in the Brazilian Network Information Center (NIC.br), a non-profit organization responsible for the planning, evaluation, and monitoring of the use of information and communication technologies (ICT) in Brazil. Here we present the approaches adopted in two projects developed to fulfil the information needs of policymakers and civil society for insights into Internet usage and Internet quality. The first experience focused on Internet usage and adopted a designed non-probability sample of internet users conducted via web self-interviewing during the COVID-19 pandemic. The second experience involved estimating from a large, non-designed organic database of Internet quality measurements taken in self-selected schools. For the Internet usage survey, a web panel, initially selected utilizing quota sampling, was surveyed to assess emerging policy-relevant topics such as privacy and e-waste among Internet users. The survey was developed in response to the urgent need for Internet usage data during the COVID-19 pandemic, in a period when traditional face-to-face household surveys were infeasible. For the Internet quality study, our experience comprised determining pseudo-weights for Brazilian public basic education schools participating in a voluntary scheme where measurements of internet quality are regularly reported to the NIC.br via the ‘Simet’ devices installed in the schools. While not all public schools have installed the Simet devices, we have developed an approach to leverage existing School Census data to estimate pseudo-weights for the participating schools, thus enabling the production of Internet quality estimates for the entire school population while minimizing response bias.
Description: Weighting is one of the major components in survey sampling. For a given sample survey, to each unit of the selected sample is attached a weight that is used to obtain estimates of population parameters of interest (e.g. means, totals, rates). The weighting process usually involves three steps: (i) obtain the design weights, which account for sample selection; (ii) adjust these weights to compensate for nonresponse; (iii) adjust the weights so that the estimates coincide to some population figures known from external trusted sources. The principle behind estimation in a probability survey is that each sample unit represents not only itself, but also several units of the survey population. The design weight of a unit usually refers to the average number of units in the population that each sampled unit represents. This weight is determined by the sampling method and is an important part of the estimation process. While the design weights can be used for estimation, most surveys produce a set of estimation weights by adjusting the design weights to improve accuracy of the final estimates. Once the final estimation weights have been calculated, they are applied to the sample data in order to compute estimates. The ILO Department of Statistics, in collaboration with the ITCILO, is proud to offer the Online course "Weighting Methods & Strategies". This course is directly linked to the course "Sampling Design: A Practical Approach" planned to take place in the spring of 2023 as both courses complement each other. Both courses are considered a learning journey that qualifies the learner to understand comprehensively Sampling design & weighting. Hence, attending both courses is strongly recommended for a fulfilling learning journey.
Target Audience: This course requires basic knowledge of statistics and probability! - It requires basic capacity to run procedures on statistical software using syntax (e.g. Stata do files, Spss syntax files, R scripts, Sas program files, etc.), and in particular with R3. The target audience includes: - Statisticians and practitioners from national statistical offices that have a role in designing household surveys samples.
Description: The course aims to enhance national capacities in the latest, most up-to-date statistical sampling techniques and methods, survey planning and data weights.
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Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
Description: Sampling is a fundamental aspect of household surveys – it allows National Statistical Offices (NSO) and researchers to collect data from a representative sample of the population. Proper sampling schemes ensure that the results of the survey are accurate and can be generalized to the entire population. Unfortunately, there have been many challenges associated with the above aspects. Currently, population censuses and consequent traditional sampling frames are facing many challenges. These include under-covered areas (such as those under conflict or difficult to access), declining response rates, and the rapidly expansion of urban sectors that get the frame outdated very soon. The census frame also usually does not contain contact information except for the addresses, which makes it difficult to reach the respondents via telephone or emails, for CATI and CAWI surveys. Sampling techniques have also been challenged, especially in efforts to reach the marginalized population. The technical meeting aims to foster knowledge exchange, explore innovative approaches, and address challenges related to sampling methodologies and the development of comprehensive sample frames.<p>Registration</p>
Description: The main objective of the course is to enhance the understanding and capacities of ILO constituents and social partners in designing and implementing household surveys and in processing sample data in line with best methodological practices. The course will enhance participant's' knowledge of the different sampling and weighting techniques, highlighting their pros and cons. In addition, it will highlight the link between sampling techniques and survey design, with a particular focus on labour force surveys (LFS), the most common source of official labour statistics across the globe. More specifically, the aims of the course are to: - Enhance understanding on sample surveys and survey designs; - Provide insights into the principles and practices of sampling; - Enrich understanding of estimation theory, methods for probability sampling, and sampling frames; - Improve understanding of different weighting strategies and treatment of unit non-response; - Increase understanding of quality dimensions and calculation of sample size for complex multi-stage designs; - Provide practical case studies on the treatment of total non-response and on weighting, making use of different sets of benchmarks available for different population sub-groups and/or for different geographical domains.
Target Audience: Important note: This course requires a basic knowledge of statistics and probability. The target audience includes: - Statisticians and practitioners from national statistical offices who have a role in designing household surveys samples and weighting survey data; - Other Statisticians from national statistical offices; Ministries of labour and other institutions involved in the production of work, social and gender-related statistics; - Employment and development policy analysts from national statistical offices, research and academic institutions, international organizations and donor organizations.
Title in Arabic: مواضيع متقدمة في العينات وحساب الأوزان وتعديلها
Organizer(s): AITRS
Description: تعتبر الدورة التدريبية الحالية المتعلقة بمواضيع متقدمة في العينات وحساب الأوزان وتعديلها مواصلة لمجهودات المعهد في دعم قدرات الاجهزة الاحصائية العربية في مجال مهم في كل الانشطة الاحصائية، وهي الثالثة في سلسلة الدورات المنعقدة حول العينات والمواضيع الخاصة بها. وسيتم تناول هذه الدورة من خلال تقديم مواضيع متقدمة في علم العينات، وذلك لبناء قدرات المتدربين بشكل افضل وزيادة خبرتهم في تطبيقات تعتبر ضرورية في مجال تصميم العينات المتكررة وحساب الاوزان. وقد اصبحت هذه التطبيقات منتشرة اقليميا ودولياً في الفترة الاخيرة نتيجة زيادة كفاءة البرمجيات الحديثة، والتطور السريع في المجال الاحصائي.
Description: Beginning in 2024, the economic directorate of the U.S. Census Bureau will introduce the Annual Integrated Economic Survey (AIES), an economy wide survey that replaces a suite of six independently designed ongoing surveys. The AIES sample design requirements are informed by the user community’s longstanding data needs (e.g., national and sub-national tabulations), as well as by extensive respondent research on collection. This paper provides an end-to-end high-level overview of the AIES probability sampling design, including determination of the sampling unit, computation of unit-level inclusion probabilities for the implement probability proportional to size sampling, stratification, allocation, and sample selection and validation. Throughout, I selectively highlight specific challenges of developing a multi-purpose business survey whose collection covers a wide range of economic sectors.
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Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
Organizer(s): Baltic-Nordic-Ukrainian Network on Survey Statistics
Description: The BNU Workshop on Survey Statistics 2022 will be organized in August 23-26, 2022, in Tartu, Estonia. The workshop will be of a hybrid type, connecting in-person participation in Tartu and online participation (via Zoom) for those registered participants who cannot attend in person. The scientific program covers both innovations in established methods on survey and official statistics and new and emerging approaches in the area. The first keynote speaker, Jean-François Beaumont, will give an online talk on inference from non-probability samples through data integration. María del Mar Rueda discusses further challenges in inference with non-probability surveys and delivers a PC lab on estimating with non-probability surveys using R. Recent advances in population statistics will be discussed by Li-Chun Zhang. In addition to the keynote talks, a number of invited and contributed papers will be presented. Further, Carl-Erik Särndal, the author of two milestone publications of 1992, the Springer book "Model-Assisted Survey Sampling" (with Bengt Swensson and Jan Wretman) and the JASA article "Calibration Estimators in Survey Sampling" (with Jean-Claude Deville), will attend the workshop. As 2022 is the jubilee year for both publications, Carl-Erik Särndal has promised to give a keynote talk on the occasion. His title is "Progress in survey science, yesterday, today, tomorrow". A round table discussion is arranged after his talk. The Workshop is organized by the Baltic-Nordic-Ukrainian (BNU) Network on Survey Statistics in cooperation with partner universities and several national statistical institutes and associations. The University of Tartu, Statistics Estonia and the University of Helsinki have primary responsibility. Today, the BNU network involves partners from Estonia, Finland, Latvia, Lithuania, Poland, Sweden and Ukraine. Baltic-Nordic co-operation on survey statistics started in 1992 by the initiative of Prof. Gunnar Kulldorff and was developed as the Baltic-Nordic-Ukrainian (BNU) Network on Survey Statistics from 1996 on. The BNU network has organized annual events since 1997. More information about the Baltic-Nordic-Ukrainian Network on Survey Statistics are available at the BNU website.
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Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
Description: Substitution of a nonresponding unit with one not originally selected in the sample is a commonly used method for dealing with unit nonresponse. Although frequently used in practice, substitution is largely neglected in the survey sampling literature. To date, few studies have attempted to develop a formal framework for describing and evaluating substitution methods, and little research has been done to improve estimates obtained through the use of substitution as a nonresponse adjustment procedure. In this presentation, I will show results from simulation and empirical studies conducted to enhance our understanding of substitution methods and present new procedures to improve them.
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Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
Description: Within the framework of its Statistical Capacity Building (StatCaB) Programme, SESRIC will organise an Online Training Course on ‘Survey Methods and Sampling’ for the benefit of National Statistical Offices (NSOs) of OIC countries on 23 – 26 May 2022. Mr. Cenker Burak Metin, Head of Survey and Sampling Design Group at the Turkish Statistical Institute (TurkStat) will conduct the course and cover the following topics: Definition of a statistical survey and basic concepts Defining the survey objectives, variables and concepts Survey planning and steps of a survey Data collection methods PAPI, CATI, CAPI and other methods Introduction to Sampling Design Implementation of Sampling Techniques Estimation theory for sample surveys The course will be conducted through a video conferencing platform by following synchronous learning and instruction approaches designed in line with the virtual training solutions undertaken by SESRIC in order to better serve the Centre’s training activities and keep participants motivated and engaged during this time of global crisis due to COVID-19. For more information on SESRIC Statistical Capacity Building (StatCaB) Programme, please visit: http://www.oicstatcom.org/statcab.php
Title in Arabic: تصميم العينات ومنهجيات المسوح في الاحصاءات الرسمية
Organizer(s): AITRS
Description: مواصلة للدورة التدريبية التي نظمها المعهد خلال الفترة 15 فبراير / شباط - 13 نيسان / ابريل 2021 حول مجال العينات بواقع 45 ساعة واعتبارا لأهمية هذا المجال لما له دور أساسي في تخطيط وبرمجة واعداد المسوح الإحصائية والمشاكل التي تواجه عملية الاستقصاء وجمع البيانات الإحصائية وأثر العينة على نتائج تلك المسوح والية اختيار المناسب منها، سينظم المعهد دورة تدريبية متقدمة حول تصميم العينات ومنهجيات المسوح في الاحصاءات الرسمية بالاضافة الى استعراض المستجدات التي طرأت في علم العينات واستخدام التقنيات الجديدة والبرمجيات الحديثة. ,تهدف هذه الدورة الى: * ترسيخ المفاهيم الضرورية لتصميم عينات المسوح الإحصائية * اعداد وتجهيز اطر المعاينة وسحب العينات منها * حساب الاوزان وتعديلها ومعايرتها * حساب التباين والدقة في التقديرات الناتجة من المسوح بالعينة * استخدام البرامج الحديثة في سحب العينات وحساب التباين * ضبط ومراقبة الجودة في كل مراحل العمل
Description: During this Global Network and ISWGHS joint webinar, we had Laura Wilson from UK Government Data Quality Hub and Emma Dickinson from Social Survey Transformation (SST) at Office for National Statistics (ONS) in UK. They talked about harnessing Respondent Centered Surveys. Throughout the survey design industry, we are experiencing a decline in response rates alongside the demand for push-to-web mixed-mode completion. The data collection world is changing and to respond to these challenges, it is necessary to combine established and innovative survey design methodologies. We must move away from the traditional approaches that hinder us from achieving our goals, such as designing surveys at desk or in the boardroom. Instead, we need to start putting the respondent first and letting them drive survey design. This is Respondent Centered Design and it is achieved by heavily involving respondents in research to establish their survey participation needs and subsequently building to meet them. Only then can we develop a survey with low burden and high-quality data. This talk explained why this shift in our design focus and practices is critical to the creation of successful surveys. It introduces and explains an innovative methodological approach called ‘Respondent Centered Design’ which is showcased in the speakers new book, ‘Respondent Centered Surveys; Stop, Listen and then Design’. The talk demonstrates its application to survey development through use of frameworks and case studies from the transformation of the UK’s Labour Force Survey from the Office for National Statistics.
Description: This webinar will focus on microdata dissemination programs with application to agriculture data with the aim to support the National Statistical Offices and line Ministries’ efforts toward unlocking access to agriculture survey data. Organized by the AGRISurvey program, managed by the Statistics Division of the FAO (ESS), the webinar entitled “Opening Access to Agricultural Survey Microdata” is designed to build advanced insight on the key elements constitutive of a microdata dissemination program, namely the access policy, microdata documentation (including the DDI-standard), microdata anonymization, and the National Data Archive (NADA) cataloguing tool. Participants will also learn about the Food and Agriculture Microdata (FAM) Catalogue, FAO's microdata dissemination platform managed by the Office of Chief Statistician (OCS). The online seminar will be an opportunity to discuss how these components interlace and, if approached jointly, may offer solutions to ensure confidentiality safeguards are in place as well as to ensure microdata dissemination programs align on best international standards. It will also serve as a platform to share experiences between agencies on both technical and organizational challenges associated with their operationalization and to discuss on methods and solutions to ensure increased access to agriculture data to the widest public. The webinar is suitable for professionals of different levels of seniority in charge of agricultural statistics production and dissemination. Acknowledging the overarching dimension of dissemination programs and the involvement of different departments and offices within the National Statistics Systems, this invitation extends to all officers from divisions and units supporting statistical dissemination programs. WHEN: November 29, 2021, from 10:00 to 13:00 (GMT+0). PRESENTATIONS: Microdata dissemination programs Statistical Disclosure Control (SDC) Microdata documentation Introduction to NADA Microdata dissemination: overview of the FAM Catalogue La diffusion des microdonnées Anonymisation des microdonnées Documentation de fichiers de microdonnées Introduction à l’Archive National de Données (NADA) Diffusion des microdonnées : vue d’ensemble du Catalogue FAM Programme de diffusion des microdonnées de l'enquête agricole annuelle (FAA) RECORDINGS: https://fao.zoom.us/rec/share/RPfxae3JRgGDIuyzohrMh_ZLUbIRZRETyfu-chupdUI73AJJo3WHbXHrgtPAh8JB.5ZltKbfHAE26WecS Access Passcode: pTZf6&amp;9v FIND OUT MORE ABOUT AGRISurvey: https://www.fao.org/in-action/agrisurvey/en/
Description: Adaptive survey designs aim to get a better balanced response by putting different effort in different groups of the population. They are effective in improving survey results and reducing survey costs. Over the last decade, a lot of methodological research has been done on this topic. In this webinar, an overview of research on adaptive survey design will be presented. After that, the implementation of adaptive survey design is demonstrated at the hand of the Dutch Health survey. In this survey a sequential mixed mode strategy CAWI followed by CAPI is applied. The feature to adapt is the CAPI follow-up. The design is developed in such a way that through stratified selection of internet nonrespondents for face to face follow-up, nonresponse bias can potentially be reduced. Mode-specific measurement errors which likely exist in many surveys, especially in the Health survey, have not received much attention in adaptive survey design. In order to separate and quantify mode-specific measurement effects and selection effects, an experiment with re-interviews is planned for the Health survey. The sampling and questionnaire design including analysis possibilities are discussed in the webinar.
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Original webpage was deleted, archived version from the Internet Archive (not a UN service): Link
Source: Eurostat (Data extracted on: 03 May 2021 )
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Organizer(s): Eurostat Icon-Institut
Description: To learn state of the art techniques in survey sampling.
Target Audience: NSI statisticians dealing with surveys faced with the challenge to change data collection methods such as mixed mode strategies and adaptive survey designs. Additionally they face the use of administrative data and big data in the survey design and weighting stage. ESTP Trainings are open to non-ESS members if capacity allows after ESS needs are fulfilled.
