17
thConference of the International Federation of Classification Societies
Book of Abstracts
IFCS 2022
Classification and Data Science in the Digital Age
v
IFCS 2022
Book of Abstracts
17th Conference of the International Federation of Classification Societies
Classification and Data Science in the Digital Age
Porto, Portugal
vii
Title: Classification and Data Science in the Digital Age - Book of Abstracts IFCS 2022
Authors: CLAD - Associação Portuguesa de Classificação e Análise de Dados Cover design: exclamação!
Printed in Portugal by Instituto Nacional de Estatística ISBN: 978-989-98955-9-1
N. DL: 500335/22 Number of copies: 350
Preface
Welcome to the 17th conference of the IFCS, IFCS 2022, held in Porto, Portugal, from July 19 to July 23, 2022 and the first IFCS conference held in Portugal. It is a joint organisation of the Portuguese Association for Classification and Data Analysis, CLAD, and the Faculty of Economics of the University of Porto, FEP-UP.
IFCS 2022 is preceeded by two half-day tutorials, one on Analysis of Data Streamsby João Gama, and another onCategorical Data Analysis and Visualization by Rosaria Lombardo and Eric J Beh, features four keynote speakers, five invited and seventy contributed sessions organised in specific topics. The Benchmarking Challenge, the Awards Session and the Presidential Address are also noteworthy.
Overall, the call for papers attracted 280 submissions, representing 42 countries and 578 different authors. The authors come from five continents, being the largest representation from Europe (68%), followed by North America (12%). Additionally to the rich scientific program the LOC has organised a number of social appealling events that will be memorable.
The 17thconference of the IFCS would not have been possible without the support of many individuals and organisations. We owe special thanks to the authors of all the submitted papers, the members of the program committee, and the reviewers for their contributions to the success of the conference. Finally, we acknowledge the institutional and industrial sponsors that contributed to the organisation of the con- ference. In particular, we thank all those at FEP-UP who enthusiastically supported the conference from the very start, contributing to its success.
This book contains the abstracts corresponding to all the presentations at the conference. It is organised in seven parts, according to the type of session. Within each session the abstracts are ordered according to the programme. The book includes also an author index.
It has been a pleasure and an honor to organise and host IFCS 2022 in Porto. It is our wish that all participants enjoy the scientific program as well as the the social events and the city of Porto and Portugal.
July 2022 The Local Organising Committee
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A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment
Afshin Ashofteh and Pedro Campos
The COVID-19 pandemic has had a direct impact on the development, production, and dissemination of official statistics. This situation led National Statistics Institutes (NSIs) to make methodological and practical choices for survey collection without the need for the direct contact of interviewing staff (i.e. remote survey data collec- tion). Mixing telephone interviews (CATI) and computer-assisted web interviewing (CAWI) with direct contact of interviewing constitute a new way for data collection at the time COVID-19 crisis. This paper presents a literature review to summarize the role of statistical classification and design weights to control coverage errors and non-response bias in mixed-mode questionnaire design. We identified 289 research articles with a computerized search over two databases, Scopus and Web of Science.
It was found that, although employing mixed-mode surveys could be considered as a substitution of traditional face-to-face interviews (CAPI), proper statistical classifi- cation of survey items and responders is important to control the nonresponse rates and coverage error risk.
Keywords: mixed-mode official surveys, item classification, weighting methods, clustering, measurement error
References
1. Ashofteh, A., and Bravo, J. M.: A study on the quality of novel coronavirus (COVID-19) official datasets. Stat. J. IAOS, vol. 36, no. 2, pp. 291–301, (2020). doi: 10.3233/SJI-200674 2. Ashofteh, A., and Bravo, J. M.: Data science training for official statistics: A new scientific
paradigm of information and knowledge development in national statistical systems. Stat. J.
IAOS, vol. 37, no. 3, pp. 771–789, (2021). doi: 10.3233/SJI-200674
3. Kim, S. and Couper,M. P.: Feasibility and Quality of a National RDD Smartphone Web Survey: Comparison With a Cell Phone CATI Survey. Soc. Sci. Comput. Rev., vol. 39, no. 6, pp. 1218–1236, (2021).
Afshin Ashofteh
Statistics Portugal (Instituto Nacional de Estatística, Departamento de Metodologia e Sistemas de Infomação) , and NOVA Information Management School (NOVA IMS) and MagIC, Universidade Nova de Lisboa, Portugal,
e-mail:afshin.ashofteh@ine.pte-mail:aashofteh@novaims.unl.pt Pedro Campos
Statistics Portugal (Instituto Nacional de Estatística, Departamento de Metodologia e Sistemas de Infomação), and University of Porto, Faculty of Economics. Universidade do Porto, Portugal, e-mail:pedro.campos@ine.pt
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