Download
12874_2024_Article_2122.pdf 1,79MB
WeightNameValue
1000 Titel
  • Health estimate differences between six independent web surveys: different web surveys, different results?
1000 Autor/in
  1. Schnell, Rainer |
  2. Klingwort, Jonas |
1000 Verlag BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-01-27
1000 Erschienen in
1000 Quellenangabe
  • 24(1):24
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12874-023-02122-0 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10821547/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:p>Most general population web surveys are based on online panels maintained by commercial survey agencies. Many of these panels are based on non-probability samples. However, survey agencies differ in their panel selection and management strategies. Little is known if these different strategies cause differences in survey estimates. This paper presents the results of a systematic study designed to analyze the differences in web survey results between agencies. Six different survey agencies were commissioned with the same web survey using an identical standardized questionnaire covering factual health items. Five surveys were fielded at the same time. A calibration approach was used to control the effect of demographics on the outcome. Overall, the results show differences between probability and non-probability surveys in health estimates, which were reduced but not eliminated by weighting. Furthermore, the differences between non-probability surveys before and after weighting are larger than expected between random samples from the same population.</jats:p>
1000 Sacherschließung
lokal Surveys and Questionnaires [MeSH]
lokal Probability sampling
lokal Humans [MeSH]
lokal Access panel
lokal Nonresponse
lokal Undercoverage
lokal Survey agencies
lokal Research Design [MeSH]
lokal Non-probability sample
lokal Health Surveys [MeSH]
lokal Research
lokal Weighting techniques
lokal Recruitment strategy
lokal Calibration
lokal Calibration [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/U2NobmVsbCwgUmFpbmVy|https://frl.publisso.de/adhoc/uri/S2xpbmd3b3J0LCBKb25hcw==
1000 Hinweis
  • DeepGreen-ID: 44f61a8e3ed04a13aa7b971b48159822 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Förderer
  1. Deutsche Forschungsgemeinschaft |
  2. Universität Duisburg-Essen |
1000 Fördernummer
  1. -
  2. -
1000 Förderprogramm
  1. -
  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Universität Duisburg-Essen |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6518242.rdf
1000 Erstellt am 2025-07-05T09:52:29.106+0200
1000 Erstellt von 322
1000 beschreibt frl:6518242
1000 Zuletzt bearbeitet 2025-08-19T19:06:45.053+0200
1000 Objekt bearb. Tue Aug 19 19:06:45 CEST 2025
1000 Vgl. frl:6518242
1000 Oai Id
  1. oai:frl.publisso.de:frl:6518242 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source