Assessing bias in online surveys using alternative survey modes

Bibliographic Data

ID21189759
AuthorsNeil H Spencer, Neil Spencer (0000-0002-6068-5887, University of Hertfordshire), Dag Sverre Syrdal (0000-0002-1339-4382, University of Hertfordshire), Matthew Coates (0000-0003-3967-4195, University of Hertfordshire), Ursula Huws (0000-0003-0774-1023, University of Hertfordshire)
Year2022
Volume16
Issue1
Publication date2022-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueWork Organisation Labour & Globalisation (JOURNAL)
Journal identifiersISSN: 1745-641X • E-ISSN: 1745-6428
PublisherPluto Journals (PUBLISHER • GB)
DOI10.13169/workorgalaboglob.16.1.0034
OpenAlexW4285262651
LanguageEN
Citations received3
References cited21

Due to concerns that respondents to online surveys are different from populations of interest, parallel offline surveys can be undertaken and results compared. In this article we create a set of principles to compare results from online surveys with those from surveys using other survey modes. Rather than just comparing estimates and confidence intervals from the different modes, these principles consider biases that each survey mode introduces and whether the results obtained are compatible with each other, given these different biases. Using the example of a survey of platform work, we demonstrate that this approach can be used effectively and be applied to a variety of social science studies that use online surveys

Confidence interval · Data science · Human–computer interaction · Statistics · Survey data collection · Survey methodology · Survey research · Applied Psychology · Computer Science · Digital Economy and Work Transformation · Mathematics · Privacy, Security, and Data Protection · Psychology · Survey Methodology and Nonresponse · Artificial Intelligence