Methodological Background 1
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Esomar/Grbn Guideline for Online Sample Quality
ESOMAR/GRBN GUIDELINE FOR ONLINE SAMPLE QUALITY ESOMAR GRBN ONLINE SAMPLE QUALITY GUIDELINE ESOMAR, the World Association for Social, Opinion and Market Research, is the essential organisation for encouraging, advancing and elevating market research: www.esomar.org. GRBN, the Global Research Business Network, connects 38 research associations and over 3500 research businesses on five continents: www.grbn.org. © 2015 ESOMAR and GRBN. Issued February 2015. This Guideline is drafted in English and the English text is the definitive version. The text may be copied, distributed and transmitted under the condition that appropriate attribution is made and the following notice is included “© 2015 ESOMAR and GRBN”. 2 ESOMAR GRBN ONLINE SAMPLE QUALITY GUIDELINE CONTENTS 1 INTRODUCTION AND SCOPE ................................................................................................... 4 2 DEFINITIONS .............................................................................................................................. 4 3 KEY REQUIREMENTS ................................................................................................................ 6 3.1 The claimed identity of each research participant should be validated. .................................................. 6 3.2 Providers must ensure that no research participant completes the same survey more than once ......... 8 3.3 Research participant engagement should be measured and reported on ............................................... 9 3.4 The identity and personal -
SAMPLING DESIGN & WEIGHTING in the Original
Appendix A 2096 APPENDIX A: SAMPLING DESIGN & WEIGHTING In the original National Science Foundation grant, support was given for a modified probability sample. Samples for the 1972 through 1974 surveys followed this design. This modified probability design, described below, introduces the quota element at the block level. The NSF renewal grant, awarded for the 1975-1977 surveys, provided funds for a full probability sample design, a design which is acknowledged to be superior. Thus, having the wherewithal to shift to a full probability sample with predesignated respondents, the 1975 and 1976 studies were conducted with a transitional sample design, viz., one-half full probability and one-half block quota. The sample was divided into two parts for several reasons: 1) to provide data for possibly interesting methodological comparisons; and 2) on the chance that there are some differences over time, that it would be possible to assign these differences to either shifts in sample designs, or changes in response patterns. For example, if the percentage of respondents who indicated that they were "very happy" increased by 10 percent between 1974 and 1976, it would be possible to determine whether it was due to changes in sample design, or an actual increase in happiness. There is considerable controversy and ambiguity about the merits of these two samples. Text book tests of significance assume full rather than modified probability samples, and simple random rather than clustered random samples. In general, the question of what to do with a mixture of samples is no easier solved than the question of what to do with the "pure" types. -
Eurobarometer 513 Climate Change
Special Eurobarometer 513 Climate Change Report Fieldwork: March - April 2021 This document does not represent the point of view of the European Commission. The interpretations and opinions contained in it are solely those of the authors. Project title Special Eurobarometer 513 Climate, Report Language version EN Catalogue number ML-03-21-256-EN-N ISBN 978-92-76-38399-4 DOI 10.2834/437 © European Union, 2021 https://www.europa.eu/eurobarometer Photo credit: Getty Images Special Eurobarometer 513 TABLE OF CONTENTS INTRODUCTION 4 EXECUTIVE SUMMARY 7 I. EUROPEAN PERCEPTIONS OF CLIMATE CHANGE 8 1. Perceptions of climate change as a global problem 9 2. Perceived seriousness of climate change 22 II. TAKING ACTION TO TACKLE CLIMATE CHANGE 26 1. Responsibility for tackling climate change 27 2. Personal action to tackle climate change 34 3. Types of individual action 39 III. ATTITUDES TO FIGHTING CLIMATE CHANGE AND THE TRANSITION TO CLEAN ENERGIES 49 1. Attitudes towards taking action on climate change 51 2. Attitudes towards reducing fossil fuel imports 54 3. Attitudes towards the economic benefits of promoting EU expertise in clean technologies outside the EU 57 4. Attitudes to public financial support for clean energies as opposed to fossil fuel subsidies 60 5. Attitudes to adapting to the adverse impacts of climate change 64 6. Attitudes to tackling climate change and environmental issues as a priority to improve public health 67 7. Attitudes on the trade-off between costs caused by climate change versus the costs of a green transition 69 IV. LOOKING TO THE FUTURE 72 1. Current national governments action to tackle climate change 73 2. -
EFAMRO / ESOMAR Position Statement on the Proposal for an Eprivacy Regulation —
EFAMRO / ESOMAR Position Statement on the Proposal for an ePrivacy Regulation — April 2017 EFAMRO/ESOMAR Position Statement on the Proposal for an ePrivacy Regulation April 2017 00. Table of contents P3 1. About EFAMRO and ESOMAR 2. Key recommendations P3 P4 3. Overview P5 4. Audience measurement research P7 5. Telephone and online research P10 6. GDPR framework for research purposes 7. List of proposed amendments P11 a. Recitals P11 b. Articles P13 2 EFAMRO/ESOMAR Position Statement on the Proposal for an ePrivacy Regulation April 2017 01. About EFAMRO and ESOMAR This position statement is submitted In particular our sector produces research on behalf of EFAMRO, the European outcomes that guide decisions of public authorities (e.g. the Eurobarometer), the non- Research Federation, and ESOMAR, profit sector including charities (e.g. political the World Association for Data, opinion polling), and business (e.g. satisfaction Research and Insights. In Europe, we surveys, product improvement research). represent the market, opinion and In a society increasingly driven by data, our profession ensures the application of appropriate social research and data analytics methodologies, rigour and provenance controls sectors, accounting for an annual thus safeguarding access to quality, relevant, turnover of €15.51 billion1. reliable, and aggregated data sets. These data sets lead to better decision making, inform targeted and cost-effective public policy, and 1 support economic development - leading to ESOMAR Global Market Research 2016 growth and jobs. 02. Key Recommendations We support the proposal for an ePrivacy Amendment of Article 8 and Recital 21 to enable Regulation to replace the ePrivacy Directive as research organisations that comply with Article this will help to create a level playing field in a true 89 of the General Data Protection Regulation European Digital Single Market whilst increasing (GDPR) to continue conducting independent the legal certainty for organisations operating in audience measurement research activities for different EU member states. -
5.1 Survey Frame Methodology
Regional Course on Statistical Business Registers: Data sources, maintenance and quality assurance Perak, Malaysia 21-25 May, 2018 4 .1 Survey fram e methodology REVIEW For sampling purposes, a snapshot of the live register at a particular point in t im e is needed. The collect ion of active statistical units in the snapshot is referred to as a frozen frame. REVIEW A sampling frame for a survey is a subset of t he frozen fram e t hat includes units and characteristics needed for t he survey. A single frozen fram e should be used for all surveys in a given reference period Creat ing sam pling fram es SPECIFICATIONS Three m ain t hings need t o be specified t o draw appropriate sampling frames: ▸ Target population (which units?) ▸ Variables of interest ▸ Reference period CHOICE OF STATISTICAL UNIT Financial data Production data Regional data Ent erpri ses are Establishments or Establishments or typically the most kind-of-activity local units should be appropriate units to units are typically used if regional use for financial data. the most appropriate disaggregation is for production data. necessary. Typically a single t ype of unit is used for each survey, but t here are except ions where t arget populat ions include m ult iple unit t ypes. CHOICE OF STATISTICAL UNIT Enterprise groups are useful for financial analyses and for studying company strategies, but they are not normally the target populations for surveys because t hey are t oo diverse and unstable. SURVEYS OF EMPLOYMENT The sam pling fram es for t hese include all active units that are em ployers. -
1988: Coverage Error in Establishment Surveys
COVERAGE ERROR IN ESTABLISHMENT SURVEYS Carl A. Konschnik U.S. Bureau of the CensusI I. Definition of Coverage Error in the survey planning stage results in a sam- pled population which is too far removed from Coverage error which includes both under- the target population. Since estimates based coverage and overcoverage, is defined as "the on data drawn from the sampled population apply error in an estimate that results from (I) fail- properly only to the sampled population, inter- ure to include all units belonging to the est in the target population dictates that the defined population or failure to include speci- sampled population be as close as practicable fied units in the conduct of the survey to the target population. Nevertheless, in the (undercoverage), and (2) inclusion of some units following discussion of the sources, measure- erroneously either because of a defective frame ment, and control of coverage error, only or because of inclusion of unspecified units or deficiencies relative to the sampled population inclusion of specified units more than once in are included. Thus, when speaking of defective the actual survey (overcoverage)" (Office of frames, only those deficiencies are discussed Federal Statistical Policy and Standards, 1978). which arise when the population which is sampled Coverage errors are closely related to but differs from the population intended to be clearly distinct from content errors, which are sampled (the sampled population). defined as the "errors of observation or objec- tive measurement, of recording, of imputation, Coverage Error Source Categories or of other processing which results in associ- ating a wrong value of the characteristic with a We will now look briefly at the two cate- specified unit" (Office of Federal Statistical gories of coverage error--defective frames and Policy and Standards, 1978). -
American Community Survey Design and Methodology (January 2014) Chapter 15: Improving Data Quality by Reducing Non-Sampling Erro
American Community Survey Design and Methodology (January 2014) Chapter 15: Improving Data Quality by Reducing Non-Sampling Error Version 2.0 January 30, 2014 ACS Design and Methodology (January 2014) – Improving Data Quality Page ii [This page intentionally left blank] Version 2.0 January 30, 2014 ACS Design and Methodology (January 2014) – Improving Data Quality Page iii Table of Contents Chapter 15: Improving Data Quality by Reducing Non-Sampling Error ............................... 1 15.1 Overview .......................................................................................................................... 1 15.2 Coverage Error ................................................................................................................. 2 15.3 Nonresponse Error............................................................................................................ 3 15.4 Measurement Error ........................................................................................................... 6 15.5 Processing Error ............................................................................................................... 7 15.6 Census Bureau Statistical Quality Standards ................................................................... 8 15.7 References ........................................................................................................................ 9 Version 2.0 January 30, 2014 ACS Design and Methodology (January 2014) – Improving Data Quality Page iv [This page intentionally left -
Solvay 224 Avenue Louise 1050 Brussels
Mobilise! Incorporating Mobile Phones in Social and Policy-oriented Surveys ALEC M GALLUP FUTURE OF 1SURVEY RESEARCH FORUM 14 October, 2009 Hôtel Solvay 224 Avenue Louise 1050 Brussels % Dear Attendee, Mobile phones have had a remarkable impact on the world in a relatively short period of time. In all surveys, the overriding consideration is to reach all members of the public, young or old, male or female, employed or self- employed. In the nineties, fixed-line telephone coverage reached almost saturation point, but times are changing. In Europe, countries such as Finland and the Czech Republic now have a majority of citizens who are "mobile-only". Furthermore, as mobile phone ownership and usage is currently higher among certain groups, such as younger members of the population, the potential arises for mobile-phone non- coverage bias. This was a topic widely debated during the 2004 US Presidential election. Further discussion and research on the topic is vital. That's why Gallup has brought together the world's leading experts to thrash out issues that will undoubtedly impact the future of social research. Earlier this year, we were saddened by the death of Alec Gallup, a consummate polling professional who served the company for 60 years. If he was still with us, he would be watching the increase of the mobile-phone population with interest. Alec Gallup understood polling from A to Z and he knew that that the future of survey research depended on methodologies that would continue to give an equal opportunity of being polled … to all members of the public Bi-annual series of seminars: Future of Surveys We would therefore like to welcome you to "The 1st Alec Gallup Future of Survey Research Forum: Incorporating Mobile Phones in Social and Policy-oriented Surveys. -
The Eu and Public Opinions: a Love-Hate Relationship?
THE EU AND PUBLIC OPINIONS: A LOVE-HATE RELATIONSHIP? Salvatore Signorelli Foreword by Julian Priestley NOVEMBER 2012 STUDIES & REPORTS 93 The EU and public opinions: A love-hate relationship? TABLE OF CONTENTS FOREWORD 4 EXECUTIVE SUMMARY 7 INTRODUCTION 9 1. European public opinion analysis instruments 12 1.1. The origins of the Eurobarometer: a brief overview 12 1.2. Deciphering European public opinion: quantitative polls 19 1.2.1. Standard EBS: regular public opinion monitoring 20 1.2.2. Special EB: in-depth thematic surveys 26 1.2.3. EB Flash: rapid thematic surveys 29 1.2.4. Sociological criticism of quantitative opinion polls 31 1.3. Qualitative Studies: analysis of reactions, feelings and motivations 33 1.4. Deliberative Polling® 37 1.5. National polls of the 27 Member States 43 2. The work of public opinion analysis within the institutions 44 2.1. The change in political context and in objectives for the EU: the rise of public opinion 44 The EU and public opinions: A love-hate relationship? 2.2. The European Commission: “driving force” of public opinion analysis in the EU 47 2.2.1. A role of interface in drafting Eurobarometer surveys 50 2.2.2. The “national” level of public opinion analysis at the Commission 52 2.3. The work of public opinion analysis at the European Parliament 54 2.3.1. An information tool 56 2.3.2. The “national” level of public opinion analysis at the European Parliament 57 2.4. The role of the other institutions 58 2.4.1. European Council 58 2.4.2. -
R(Y NONRESPONSE in SURVEY RESEARCH Proceedings of the Eighth International Workshop on Household Survey Nonresponse 24-26 September 1997
ZUMA Zentrum für Umfragen, Melhoden und Analysen No. 4 r(y NONRESPONSE IN SURVEY RESEARCH Proceedings of the Eighth International Workshop on Household Survey Nonresponse 24-26 September 1997 Edited by Achim Koch and Rolf Porst Copyright O 1998 by ZUMA, Mannheini, Gerinany All rights reserved. No part of tliis book rnay be reproduced or utilized in any form or by aiiy means, electronic or mechanical, including photocopying, recording, or by any inforniation Storage and retrieval System, without permission in writing froni the publisher. Editors: Achim Koch and Rolf Porst Publisher: Zentrum für Umfragen, Methoden und Analysen (ZUMA) ZUMA is a member of the Gesellschaft Sozialwissenschaftlicher Infrastruktureinrichtungen e.V. (GESIS) ZUMA Board Chair: Prof. Dr. Max Kaase Dii-ector: Prof. Dr. Peter Ph. Mohlcr P.O. Box 12 21 55 D - 68072.-Mannheim Germany Phone: +49-62 1- 1246-0 Fax: +49-62 1- 1246- 100 Internet: http://www.social-science-gesis.de/ Printed by Druck & Kopie hanel, Mannheim ISBN 3-924220-15-8 Contents Preface and Acknowledgements Current Issues in Household Survey Nonresponse at Statistics Canada Larry Swin und David Dolson Assessment of Efforts to Reduce Nonresponse Bias: 1996 Survey of Income and Program Participation (SIPP) Preston. Jay Waite, Vicki J. Huggi~isund Stephen 1'. Mnck Tlie Impact of Nonresponse on the Unemployment Rate in the Current Population Survey (CPS) Ciyde Tucker arzd Brian A. Harris-Kojetin An Evaluation of Unit Nonresponse Bias in the Italian Households Budget Survey Claudio Ceccarelli, Giuliana Coccia and Fahio Crescetzzi Nonresponse in the 1996 Income Survey (Supplement to the Microcensus) Eva Huvasi anci Acfhnz Marron The Stability ol' Nonresponse Rates According to Socio-Dernographic Categories Metku Znletel anci Vasju Vehovar Understanding Household Survey Nonresponse Through Geo-demographic Coding Schemes Jolin King Response Distributions when TDE is lntroduced Hikan L. -
Trust in Public Institutions: Trends and Implications for Economic Security
POLICY BRIEF NO108 Trust in public institutions: Trends and implications for economic security WHY SHOULD WE CARE ABOUT TRUST? Trust is integral to the functioning of any society. Trust in each Summary other, in our public institutions and in our leaders are all essential The legitimacy of public institutions is crucial for ingredients for social and economic progress, allowing people to building peaceful and inclusive societies. While levels of cooperate with and express solidarity for one another.1 It allows trust in institutions vary significantly across countries, public bodies to plan and execute policies and deliver services. Greater public trust has been found to improve compliance in regu- opinion surveys suggest that there has been a decline lations and tax collections, even respect for property rights.2 It also in trust in public institutions in recent decades. gives confidence to consumers and investors, crucial to creating Economic insecurity—which the COVID-19 crisis jobs and the functioning of economies more broadly. Success in threatens to exacerbate—and perceptions of poor or achieving each of the Sustainable Development Goals (SDGs)— corrupt government performance undermine the social from eliminating poverty (SDG1), to combatting climate change contract and are closely linked to declines in institutional (SDG13), to building peaceful and inclusive societies (SDG16)— trust. Rebuilding public trust in the light of the current will depend on citizens’ and businesses’ trust in public institutions crisis demands services that work for everyone and and in each other. jobs that provide income security, as well as more Governments have also drawn on public trust to effectively address every stage of the COVID-19 pandemic response—from inclusive institutions. -
Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage Across Countries and Over Time
www.ssoar.info Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage across Countries and over Time Mohorko, Anja; Leeuw, Edith de; Hox, Joop Veröffentlichungsversion / Published Version Zeitschriftenartikel / journal article Empfohlene Zitierung / Suggested Citation: Mohorko, A., Leeuw, E. d., & Hox, J. (2013). Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage across Countries and over Time. Survey Methods: Insights from the Field, 1-13. https://doi.org/10.13094/SMIF-2013-00002 Nutzungsbedingungen: Terms of use: Dieser Text wird unter einer CC BY-NC-ND Lizenz This document is made available under a CC BY-NC-ND Licence (Namensnennung-Nicht-kommerziell-Keine Bearbeitung) zur (Attribution-Non Comercial-NoDerivatives). For more Information Verfügung gestellt. Nähere Auskünfte zu den CC-Lizenzen finden see: Sie hier: https://creativecommons.org/licenses/by-nc-nd/4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/deed.de Diese Version ist zitierbar unter / This version is citable under: https://nbn-resolving.org/urn:nbn:de:0168-ssoar-333873 Survey Methods: Insights from the Field Anja Mohorko, Department of Methodology and Statistics, Utrecht University Edith de Leeuw, Department of Methodology and Statistics, Utrecht University Joop Hox, Department of Methodology and Statistics, Utrecht University 25.01.2013 How to cite this article: Mohorko, A., de Leeuw, E., & Hox, J. (2013). Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage across Countries and over Time. Survey Methods: Insights from the Field. Retrieved from http://surveyinsights.org/?p=828 Abstract With the decrease of landline phones in the last decade, telephone survey methodologists face a new challenge to overcome coverage bias.