A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment

Afshin Ashofteh; Pedro Campos

doi:10.1007/978-3-031-09034-9_7

A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment

Afshin Ashofteh, Pedro Campos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

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 collection). 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 cover-age 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 classification of survey items and responders is important to control the nonresponse rates and coverage error risk.

Original language	English
Title of host publication	Classification and Data Science in the Digital Age
Editors	Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent
Place of Publication	Gewerbestrasse, Switzerland
Publisher	Springer, Cham
Pages	53-61
Number of pages	9
ISBN (Electronic)	978-3-031-09034-9
ISBN (Print)	978-3-031-09033-2
DOIs	https://doi.org/10.1007/978-3-031-09034-9_7
Publication status	Published - 8 Dec 2023
Event	17th Conference of the International Federation of Classification Societies: Classification and Data Science in the Digital Age - Faculdade de Economia da Universidade do Porto, Porto, Portugal Duration: 19 Jul 2022 → 23 Jul 2022 Conference number: 17 https://ifcs2022.fep.up.pt/

Publication series

Name	Studies in Classification, Data Analysis, and Knowledge Organization
Publisher	Springer Cham
ISSN (Print)	1431-8814
ISSN (Electronic)	2198-3321

Conference

Conference	17th Conference of the International Federation of Classification Societies
Abbreviated title	IFCS 2022
Country/Territory	Portugal
City	Porto
Period	19/07/22 → 23/07/22
Internet address	https://ifcs2022.fep.up.pt/

Keywords

Mixed Mode
Classification
Clustering
Measurement Error
mixed-mode official surveys
item classification
weighting methods

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-09034-9_7Licence: CC BY

A_Review_on_Official_Survey_Item_Classification_for_Mixed_Mode_Effects_AdjustmentFinal published version, 680 KBLicence: CC BY

Cite this

Ashofteh, A., & Campos, P. (2023). A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. In P. Brito, J. G. Dias, B. Lausen, A. Montanari, & R. Nugent (Eds.), Classification and Data Science in the Digital Age (pp. 53-61). (Studies in Classification, Data Analysis, and Knowledge Organization). Springer, Cham. https://doi.org/10.1007/978-3-031-09034-9_7

Ashofteh, Afshin ; Campos, Pedro. / A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. Classification and Data Science in the Digital Age. editor / Paula Brito ; José G. Dias ; Berthold Lausen ; Angela Montanari ; Rebecca Nugent. Gewerbestrasse, Switzerland : Springer, Cham, 2023. pp. 53-61 (Studies in Classification, Data Analysis, and Knowledge Organization).

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Ashofteh, A & Campos, P 2023, A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. in P Brito, JG Dias, B Lausen, A Montanari & R Nugent (eds), Classification and Data Science in the Digital Age. Studies in Classification, Data Analysis, and Knowledge Organization, Springer, Cham, Gewerbestrasse, Switzerland, pp. 53-61, 17th Conference of the International Federation of Classification Societies, Porto, Portugal, 19/07/22. https://doi.org/10.1007/978-3-031-09034-9_7

A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. / Ashofteh, Afshin; Campos, Pedro.
Classification and Data Science in the Digital Age. ed. / Paula Brito; José G. Dias; Berthold Lausen; Angela Montanari; Rebecca Nugent. Gewerbestrasse, Switzerland: Springer, Cham, 2023. p. 53-61 (Studies in Classification, Data Analysis, and Knowledge Organization).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Campos, Pedro

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N2 - 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 collection). 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 cover-age 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 classification of survey items and responders is important to control the nonresponse rates and coverage error risk.

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Ashofteh A, Campos P. A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment. In Brito P, Dias JG, Lausen B, Montanari A, Nugent R, editors, Classification and Data Science in the Digital Age. Gewerbestrasse, Switzerland: Springer, Cham. 2023. p. 53-61. (Studies in Classification, Data Analysis, and Knowledge Organization). doi: 10.1007/978-3-031-09034-9_7

A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment

Abstract

Publication series

Conference

Keywords

UN SDGs

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