[
Allum, N., F. Conrad, and A. Wenz. 2018. “Consequences of Mid-Stream Mode-Switching in a Panel Survey.” Survey Research Methods 12: 43–58. DOI: https://doi.org/10.18148/srm/2018.v12i1.6779.
]Search in Google Scholar
[
Antoun, C. 2015. Who are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences Across Internet-Use Subgroups in the U.S.” In Mobile Research Methods: Opportunities and Challenges of Mobile Research Methodologies by D. Toninelli, R. Pinter, and P. Pedraza: 99–117. Ubiquity Press. DOI: http://dx.doi.org/10.5334/bar.g.10.5334/bar.g
]Search in Google Scholar
[
Antoun, C., and A. Cernat. 2020. “Factors Affecting Completion Times: A Comparative Analysis of Smartphone and PC Web Surveys.” Social Science Computer Review 38: 477–489. DOI: https://doi.org/10.1177/0894439318823703.
]Search in Google Scholar
[
Antoun, C., F.G. Conrad, M.P. Couper, and T.B. West. 2019. “Simultaneous Estimation of Multiple Sources of Error in a Smartphone-Based Survey.” Journal of Survey Statistics and Methodology 7: 93–117. DOI: https://doi.org/10.1093/jssam/smy002.
]Search in Google Scholar
[
Antoun, C., M.P. Couper, and F.G. Conrad. 2017. “Effects of Mobile versus PC Web on Survey Response Quality.” Public Opinion Quarterly 81: 280 – 306. DOI: https://doi.org/10.1093/poq/nfw088.
]Search in Google Scholar
[
Antoun, C., J. Katz, J. Argueta, and L. Wang. 2018. “Design Heuristics for Effective Smartphone Questionnaires.” Social Science Computer Review 36: 557–574. DOI: https://doi.org/10.1177/0894439317727072.
]Search in Google Scholar
[
Baron, R.M. and D.A. Kenny. 1986. “The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations.” Journal of Personality and Social Psychology 51: 1173–1182. DOI: https://doi.org/10.1037/0022-3514.51.6.1173.
]Search in Google Scholar
[
Bosnjak, M., G. Metzger, and L. Gräf. 2010. “Understanding the Willingness to Participate in Mobile Surveys: Exploring the Role of Utilitarian, Affective, Hedonic, Social, Self-Expressive, and Trust-Related Factors.” Social Science Computer Review 28: 350–370. DOI: https://doi.org/10.1177/0894439309353395.
]Search in Google Scholar
[
Bradburn, N. 1978. Respondent burden. Health Survey Research Methods, DHEW Publication No. 79-3207: 35–40. Washington, DC: U.S. Department of Health, Education, and Welfare. Available at: http://www.asasrms.org/Proceedings/papers/1978_007.pdf (accessed March 2022).
]Search in Google Scholar
[
Buskirk, T.D., and C. Andrus. 2012. “Online Surveys Aren’t Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone vs. Computer-based Online Surveys”. In JSM Proceedings, Survey Research Methods Section. Alexandria, VA: American Statistical Association: 5678–5691. Available at: http://www.asasrms.org/Proceedings/y2012f.html (accessed March 2022).
]Search in Google Scholar
[
Buskirk, T.D. and C. Andrus. 2014. “Making Mobile Browser Surveys Smarter: Results from a Randomized Experiment Comparing Online Surveys Completed via Computer or Smartphone.” Field Methods 26: 322–342. DOI: https://doi.org/10.1177/1525822X14526146.
]Search in Google Scholar
[
Callegaro, M. 2010. “Do You Know Which Device Your Respondent Has Used to Take Your Online Survey?” Survey Practice 3: 1–12. DOI: https://doi.org/10.29115/sp-2010-0028.
]Search in Google Scholar
[
Callegaro, M. 2013. “From Mixed-Mode to Multiple Devices: Web Surveys, Smartphone Surveys and Apps: Has the Respondent Gone Ahead of Us in Answering Surveys?”, International Journal of Market Research 55: 317–320. DOI: https://doi.org/10.2501/IJMR-2013-026.
]Search in Google Scholar
[
Callegaro, M., K. Manfreda, and V. Vehovar. 2015. Web Survey Methodology. London, UK: SAGE.10.4135/9781529799651
]Search in Google Scholar
[
Couper, M.P., C. Antoun, and A. Mavletova. 2017. “Mobile Web Surveys.” In Total Survey Error in Practice edited by P.P. Biemer, E.D. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L.E. Lyberg, N.C. Tucker, and B.T. West: 133–154. Hoboken, NJ: Wiley. DOI: https://doi.org/10.1002/9781119041702.ch7.
]Search in Google Scholar
[
Couper, M.P. and G.J. Peterson. 2017. “Why Do Web Surveys Take Longer on Smartphones?” Social Science Computer Review 35: 357–377. DOI: https://doi.org/10.1177/0894439316629932.
]Search in Google Scholar
[
De Bruijne, M. and A. Wijnant. 2014a. “Mobile Response in Web Panels.” Social Science Computer Review 32: 728–742. DOI: https://doi.org/10.1177/0894439314525918.
]Search in Google Scholar
[
De Bruijne, M. and A. Wijnant, A. 2014b. “Improving Response Rates and Questionnaire Design for Mobile Web Surveys.” Public Opinion Quarterly 78: 951–962. DOI: https://doi.org/10.1093/poq/nfu046.
]Search in Google Scholar
[
De Leeuw, E.D. and P. Lugtig. 2014. Dropouts in Longitudinal Surveys. Wiley StatsRef: Statistics Reference Online. John Wiley & Sons, Ltd. DOI: 10.1002/9781118445112.stat06661.pub2.
]Otwórz DOISearch in Google Scholar
[
Dillman, D.A., M.D. Sinclair, and J.R. Clark. 1993. “Effects of Questionnaire Length, Respondent-friendly Design, and a Difficult Question on Response Rates for Occupant-addressed Census Mail Surveys.” Public Opinion Quarterly 57: 289-304. DOI: 10.1086/269376.
]Otwórz DOISearch in Google Scholar
[
Dillman, D.A., J.D. Smyth, and L.M. Christian. 2014. Internet, Mail, and Mixed-mode Surveys: The Tailored Design Method. Hoboken, NJ: John Wiley & Sons.
]Search in Google Scholar
[
Elevelt, A., P. Lugtig, and V. Toepoel. 2019. “Doing a Time Use Survey on Smartphones Only: What Factors Predict Nonresponse at Different Stages of the Survey Process?” Survey Research Methods 13: 195–213. DOI: https://doi.org/10.18148/srm/2019.v13i2.7385.
]Search in Google Scholar
[
Freese, J. and A. Branigan. 2012. “Cognitive Skills and Survey Nonresponse –– Evidence from Two Longitudinal Studies in the United States.” EurAmerica 42: 221–247. Available at: https://www.ea.sinica.edu.tw/eu_file/134009378914.pdf.
]Search in Google Scholar
[
Galesic, M. 2006. “Dropouts on the Web: Effects of Interest and Burden Experienced during an Online Survey.” Journal of Official Statistics 22: 313–328. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/dropouts-onthe-web-effects-of-interest-and-burden-experienced-during-an-online-survey.pdf
]Search in Google Scholar
[
Galesic, M., and M. Bosnjak. 2009. “Effects of Questionnaire Length on Participation and Indicators of Response Quality in a Web Survey.” Public Opinion Quarterly 73: 349–360. DOI: https://doi.org/10.1093/poq/nfp031.
]Search in Google Scholar
[
Geisen, E., and J.R. Bergstrom. 2017. Usability Testing for Survey Research. Burlington, MA: Morgan Kaufmann.
]Search in Google Scholar
[
Groves, R., S. Presser, and S. Dipko. 2004. “The Role of Topic Interest in Survey Participation Decisions.” Public Opinion Quarterly 68: 2–31. DOI: https://doi.org/10.1093/poq/nfh002.
]Search in Google Scholar
[
Guidry, K.R. 2012. “Response Quality and Demographic Characteristics of Respondents Using a Mobile Device on a Web-Based Survey?” Presentation at the American Association for Public Opinion Research’s 67th Annual Conference. May 18, Orlando, FL, U.S.A. Available at: https://www.aapor.org/AAPOR_Main/media/AnnualMeeting-Proceedings/2012/01_KRGuidry_F1_Mobile-Device-Respondents.pdf (accessed March 2022).
]Search in Google Scholar
[
Gummer, T., and J. Daikeler. 2020. “A Note on How Prior Survey Experience with Self-Administered Panel Surveys Affects Attrition in Different Modes.” Social Science Computer Review 38: 490–498. DOI: https://doi.org/10.1177/0894439318816986.
]Search in Google Scholar
[
Haraldsen, G. 2004. “Searching for Response Burdens in Focus Groups with Business Respondents.” In Proceedings of the QUEST 2003: Proceedings of the 4th Conference on Questionnaire Evaluation Standards, 21-23 October 2003, edited by P. Prüfer, M. Rexroth, and F.J.J. Fowler: 13–123. Mannheim: Zentrum für Umfragen, Methoden und Analysen -ZUMA-. Available at: https://nbn-resolving.org/urn:nbn:de:0168-ssoar-49200-6 (accessed August 2021).
]Search in Google Scholar
[
Harder, V.S., E.A. Stuart, and J.C. Anthony. 2010. “Propensity Score Techniques and the Assessment of Measured Covariate Balance to Test Causal Associations in Psychological Research.” Psychological Methods 15: 234–249. DOI: https://doi.org/10.1037/a0019623.293669820822250
]Search in Google Scholar
[
Hayes, A.F. 2017. Introduction to Mediation, Moderation, and Conditional Process Analysis. New York, NY: The Guilford Press.
]Search in Google Scholar
[
Herzing, J.M.E. 2019. Mobile Web Surveys. FORS Guide No. 01, Version 1.0. Lausanne: Swiss Centre of Expertise in the Social Sciences FORS. DOI: https://doi.org/10.24449/FG-2019-00001.
]Search in Google Scholar
[
Hill, D.H. and R.J. Willis. 2001. “Reducing Panel Attrition. A Search for Effective Policy Instruments.” Journal of Human Resources 26: 416–438. DOI: https://doi.org/10.2307/3069625.
]Search in Google Scholar
[
Hoogendoorn, A.W., and D. Sikkel. 1998. “Response Burden and Panel Attrition.” Journal of Official Statistics 14: 189–205. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/response-burden-and-panel-attrition.pdf
]Search in Google Scholar
[
Hox, J., E.D. de Leeuw, and T. Klausch. 2017. “Mixed Mode Research: Issues in Design and Analysis.” In Total survey error in practice edited by P.P. Biemer, E.D. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L.E. Lyberg, N.C. Tucker, and B.T. West: 511–530. Hoboken, NJ: Wiley. DOI: https://doi.org/10.1002/9781119041702.ch23.
]Search in Google Scholar
[
Jäckle, A., J. Burton, M.P. Couper, and C. Lessof. 2019. “Participation in a Mobile App Survey to Collect Expenditure Data as Part of a Large-Scale Probability Household Panel: Coverage and Participation Rates and Biases.” Survey Research Methods 13: 23–44. DOI: https://doi.org/10.18148/srm/2019.v1i1.7297
]Search in Google Scholar
[
Jäckle, A., A. Gaia, and M. Benzeval. 2018. The Use of New Technologies to Measure Socioeconomic and Environmental Concepts in Longitudinal Studies. CLOSER Resource report. London, UK: UCL, Closer, Institute of Education. Available at: https://www.closer.ac.uk/wp-content/uploads/CLOSER-resource-The-use-of-new-technology-to-measure-socio-economic-and-environmental-concepts.pdf (accessed March 2022).
]Search in Google Scholar
[
Jacobsen, J. and S. Kühne. 2021. Using a Mobile App When Surveying Highly Mobile Populations: Panel Attrition, Consent, and Interviewer Effects in a Survey of Refugees. Social Science Computer Review 39: 721–743. DOI: https://doi.org/10.1177/0894439320985250.
]Search in Google Scholar
[
Johnson, A., F. Kelly, and S. Stevens. 2012. “Modular Survey Design for Mobile Devices.” Presentation at the CASRO Online Conference 2012, March 7–8, Las Vegas, NE, U.S.A. Available at: https://c.ymcdn.com/sites/www.casro.org/resource/collection/E270CC91-6B72-4C37-BCC0-5503/CBB66C55/Paper_-_Frank_Kelly_and_Alex_-Johnson_-_Lightspeed_Research_and_Kantar_Operations.pdf.
]Search in Google Scholar
[
Kalton, G., J. Lepkowski, G.E. Montanari, and D. Maligalig. 1990. “Characteristics of Second Wave Nonrespondents in a Panel Survey.” In Proceedings of the Survey Research Methods Section: American Statistical Association: 462–467. In JSM Proceedings, Survery Research Methods Section. Alexandria, VA, U.S.A. Available at: http://www.asasrms.org/Proceedings/y1990f.html (accessed August 2021).
]Search in Google Scholar
[
Keusch, F., B. Struminskaya, C. Antoun, M.P. Couper, and F. Kreuter. 2019. “Willingness to Participate in Passive Mobile Data Collection.” Public Opinion Quarterly 83: 210–235. DOI: https://doi.org/10.1093/poq/nfz007.663976531337924
]Search in Google Scholar
[
Keusch, F. and T. Yan. 2017. “Web versus Mobile Web: An Experimental Study of Device Effects and Self-Selection Effects.” Social Science Computer Review 35: 751–769. DOI: https://doi.org/10.1177/0894439316675566.
]Search in Google Scholar
[
Klausch, T., J. Hox, and B. Schouten. 2015. “Selection Error in Single- and Mixed Mode Surveys of the Dutch General Population.” Journal of the Royal Statistical Society Series A 178: 945–961. DOI: https://doi.org/10.1111/rssa.12102.
]Search in Google Scholar
[
Kleinert, C., B. Christoph, and M. Ruland. 2019. “Experimental Evidence on Immediate and Long-term Consequences of Test-induced Respondent Burden for Panel Attrition.” Sociological Methods and Research: 1–32. DOI: https://doi.org/10.1177/0049124119826145.
]Search in Google Scholar
[
Kreuter, F., G.-C. Haas, F. Keusch, S. Bähr, and M. Trappmann. 2018. “Collecting Survey and Smartphone Sensor Data with an App: Opportunities and Challenges Around Privacy and Informed Consent.” Social Science Computer Review 38: 533–549. DOI: https://doi.org/10.1177/0894439318816389.
]Search in Google Scholar
[
Laurie, H. 2008. “Handbook of Longitudinal Research: Design, Measurement, and Analysis.” In Minimizing Panel Attrition edited by S. Menard: 167–184. Elsevier.
]Search in Google Scholar
[
Laurie, H., R. Smith, and L. Scott. 1999. ‘‘Strategies for Reducing Nonresponse in a Longitudinal Panel Survey.’’ Journal of Official Statistics 15: 269–282.
]Search in Google Scholar
[
Lawes, M., C. Hetschko, J.W. Sakshaug, and S. Griessemer. 2021. “Contact Modes and Participation in App-based Smartphone Surveys: Evidence from a Large-scale Experiment.” Social Science Computer Review. DOI: https://doi.org/10.1177/0894439321993832.
]Search in Google Scholar
[
Lee, H., S. Kim, M. Couper, and Y. Woo. 2019. “Experimental Comparison of PC Web, Smartphone Web, and Telephone Surveys in the New Technology Era.” Social Science Computer Review 37: 234–247. DOI: https://doi.org/10.1177/0894439318756867.
]Search in Google Scholar
[
Lemay, M. 2010. ‘‘Understanding the Mechanism of Panel Attrition.’’ Unpublished Doctoral thesis, Doctor of Philosophy, University of Maryland, College Park, MD.
]Search in Google Scholar
[
Lepkowski, J.M. and M.P. Couper. 2002. “Nonresponse in the Second Wave of Longitudinal Household Surveys.” In Survey Nonresponse edited by R.M. Groves, D.A. Dillman, J.E. Eltinge, and R.J.A. Little: 259–272. New York: Wiley.
]Search in Google Scholar
[
Link, M.W., J. Murphy, M.F. Schober, T.D. Buskirk, J. Hunter Childs, and C. Langer Tesfaye. 2014. “Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys.” Public Opinion Quarterly 78: 779–787. DOI: https://doi.org/10.1093/poq/nfu054.
]Search in Google Scholar
[
Lipps, O. 2009. Attrition of Households and Individuals in Panel Surveys. SOEP- Papers 164. Berlin: DIW. Available at: http://www.diw.de/documents/publikationen/73/diw_01.c.96125.de/diw_sp0164.pdf (accessed March 2022).
]Search in Google Scholar
[
Loosveldt, G. and A. Carton. 2001. “An Empirical Test of a Limited Model for Panel Refusals.” International Journal of Public Opinion Research 13:173–185. DOI: https://doi.org/10.1093/ijpor/13.2.173
]Search in Google Scholar
[
Loosveldt, G., J. Pickery, and J. Billiet. 2002. “Item Nonresponse as a Predictor of Unit Nonresponse in a Panel Survey.” Journal of Official Statistics 18: 545–557. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/item-nonresponse-as-a-predictor-of-unit-nonresponse-in-a-panel-survey.pdf.
]Search in Google Scholar
[
Lugtig, P. 2014. “Panel Attrition: Separating Stayers, Fast Attriters, Gradual Attriters, and Lurkers.” Sociological Methods & Research 43: 699–723. DOI: https://doi.org/10.1177/0049124113520305
]Search in Google Scholar
[
Lugtig, P. 2021. “What Panel Surveys and Smartphone-App Studies can Learn from Each Other.” Presentation at the 9th Conference of the European Survey Research Association, Online, July 9. Available at: https://www.europeansurveyresearch.org/conferences/program2021?sess=29#218 (accessed March 2022).
]Search in Google Scholar
[
Lugtig, P. and V. Toepoel. 2016. “The Use of PCs, Smartphones, and Tablets in a Probability-Based Panel Survey: Effects on Survey Measurement Error.” Social Science Computer Review, 34: 78–94. DOI: https://doi.org/10.1177/0894439315574248.
]Search in Google Scholar
[
Lynn, P. 2008. “The Problem of Nonresponse.” In International Handbook of Survey Methodology edited by E.D. de Leeuw, J.J. Hox, and D.A. Dillman: 35–55. New York: Psychology Press.
]Search in Google Scholar
[
Lynn, P. 2014. “Longer Interviews May Not Affect Subsequent Survey Participation Propensity.” Public Opinion Quarterly 78: 500–509. DOI: http://dx.doi.org/10.1093/poq/nfu015.10.1093/poq/nfu015
]Search in Google Scholar
[
Marcus, B., M. Bosnjak, S. Lindner, S. Pilischenko, and A. Schütz. 2007. “Compensating for Low Topic Interest and Long Surveys. A Field Experiment on Nonresponse in Web Surveys.” Social Science Computer Review 25: 372–383. DOI: https://doi.org/10.1177/0894439307297606.
]Search in Google Scholar
[
Maslovskaya, O., G.B. Durrant, P.W.F. Smith, T. Hanson, and A. Villar. 2019. “What are the Characteristics of Respondents Using Different Devices in Mixed-Device Online Surveys? Evidence from Six UK Surveys.” International Statistical Review 87: 326–346. DOI: https://doi.org/10.1111/insr.12311.
]Search in Google Scholar
[
Mavletova, A. 2013. “Data Quality in PC and Mobile Web Surveys.” Social Science Computer Review 31: 725–743. DOI: https://doi.org/10.1177/0894439313485201.
]Search in Google Scholar
[
Mavletova, A. and M.P. Couper. 2013. “Sensitive Topics in PC Web and Mobile WebSurveys: Is there a Difference?” Survey Research Methods 7: 191–205. DOI: https://doi.org/10.18148/srm/2013.v7i3.5458.
]Search in Google Scholar
[
Mavletova, A. and M.P. Couper. 2015. “A Meta-Analysis of Breakoff Rates.” In Mobile Research Methods: Opportunities and Challenges of Mobile Research Methodologies edited by D. Toninelli, R. Pinter, and P. Pedraza: 81–98. Ubiquity Press. DOI: https://doi.org/10.5334/bar.f.
]Search in Google Scholar
[
Mavletova, A., M.P. Couper, and D. Lebedev. 2018. “Grid and Item-by-Item Formats in PC and Mobile Web Surveys.” Social Science Computer Review 36: 647–668. DOI: https://doi.org/10.1177/0894439317735307.
]Search in Google Scholar
[
Mulder, J. and M. de Bruijne. 2019. “Willingness of Online Respondents to Participate in Alternative Modes of Data Collection.” Survey Practice 12: 1–11. DOI: https://doi.org/10.29115/SP-2019-0001.
]Search in Google Scholar
[
Office of Management and Budget. 2006. Standards and Guidelines for Statistical Surveys. Executive Office of the President of the United States. Available at: https://unstats.un.org/unsd/dnss/docs-nqaf/USA_standards_stat_surveys.pdf (accessed August 2021).
]Search in Google Scholar
[
Olsen, R.J. 2005. “The Problem of Respondent Attrition: Survey Methodology is the Key.” Monthly Labor Review 128: 63–70. Available at: http://www.jstor.org/stable/23804052 (accessed March 2022).
]Search in Google Scholar
[
Peytchev, A. 2009. “Survey Breakoff.” Public Opinion Quarterly 73: 74–97. DOI: https://doi.org/10.1093/poq/nfp014.
]Search in Google Scholar
[
Peytchev, A. and C.A. Hill. 2010. “Experiments in Mobile Web Survey Design: Similarities to Other Modes and Unique Considerations.” Social Science Computer Review 28: 319–335. DOI: https://doi.org/10.1177/0894439309353037.
]Search in Google Scholar
[
Pinter, R. 2015. “Willingness of Online Access Panel Members to Participate in Smartphone Application-Based Research.” In Mobile Research Methods, edited by D. Toninelli, R. Pinter, and P. de Pedraza: 141–156. London: Ubiquity Press.
]Search in Google Scholar
[
Read, B. 2019. “Respondent Burden in a Mobile App: Evidence from a Shopping Receipt Scanning Study.” Survey Research Methods 13: 45–71. DOI: https://doi.org/10.18148/srm/2019.v1i1.7379.
]Search in Google Scholar
[
Revilla, M., M.P. Couper, and C. Ochoa. 2019. “Willingness of Online Panelists to Perform Additional Tasks.” Methods, Data, Analyses 13: 223–252. DOI: https://doi.org/10.12758/mda.2018.01.
]Search in Google Scholar
[
Revilla, M. and C. Ochoa. 2015. “What are the Links in a Web Survey among Response Time, Quality, and Auto-Evaluation of the Efforts Done?” Social Science Computer Review 33: 97–114. DOI: https://doi.org/10.1177/0894439314531214.
]Search in Google Scholar
[
Revilla, M., C. Ochoa, and G. Loewe. 2017. “Using Passive Data from a Meter to Complement Survey Data in Order to Study Online Behavior.” Social Science Computer Review 35: 521–536. DOI: https://doi.org/10.1177/0894439316638457.
]Search in Google Scholar
[
Revilla, M., D. Toninelli, and C. Ochoa. 2016. “PCs versus Smartphones in Answering Web Surveys: Does the Device Make a Difference?” Survey Practice 9: 1–6. DOI: https://doi.org/10.29115/sp-2016-0021.
]Search in Google Scholar
[
Roberts, C., Vandenplas, C., and J. Herzing. 2020. “A Validation of R-indicators as a Measure of the Risk of Bias using Data from a Non-response Follow-up Survey.” Journal of Official Statistics 36: 675-701. DOI: https://doi.org/10.2478/jos-2020-0034.
]Search in Google Scholar
[
Rosenbaum, P.R., and D.B. Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70: 41–55. DOI: https://doi.org/10.1093/biomet/70.1.41.
]Search in Google Scholar
[
Sakshaug, J.W., and F. Kreuter. 2011. “Using Paradata and Other Auxiliary Data to Examine Mode Switch Nonresponse in a “Recruit-and-Switch” Telephone Survey.” Journal of Official Statistics 27: 339–357. Available at: https://www.scb.se/conten-tassets/ca21efb41fee47d293bbee5bf7be7fb3/using-paradata-and-other-auxiliary-data-to-examine-mode-switch-nonresponse-in-a-34recruit-and-switch34-telephone-survey.pdf.
]Search in Google Scholar
[
Sakshaug, J.W., T. Yan, and R. Tourangeau. 2010. “Nonresponse Error, Measurement Error, and Mode of Data Collection: Tradeoffs in a Multi-Mode Survey of Sensitive and Non-Sensitive Items.” Public Opinion Quarterly 74: 907–933. DOI: https://doi.org/10.1093/poq/nfq057.
]Search in Google Scholar
[
Scherpenzeel, A. 2017. “Mixing Online Panel Data Collection with Innovative Methods.” In Methodische Probleme von Mixed-Mode-Ansätzen in der Umfrageforschung [Methodological Problems of Mixed-Mode Approaches in Survey Research], edited by S. Eifler and F. Faulbaum: 27–49. Wiesbaden: Springer.10.1007/978-3-658-15834-7_2
]Search in Google Scholar
[
Stapleton, C.E. 2013. “The Smart(phone) Way to Collect Survey Data.” Survey Practice 6: 1–7. DOI: https://doi.org/10.29115/sp-2013-0011.
]Search in Google Scholar
[
Struminskaya, B., K. Weyandt, and M. Bosnjak. 2015. “The Effects of Questionnaire Completion using Mobile Devices on Data Quality. Evidence from a Probability-Based General Population Panel.” Methods, Data, Analyses 9: 261–292. DOI: https://doi.org/10.12758/mda.2015.014.
]Search in Google Scholar
[
Struminskaya, B., Toepoel, V., Lutgtig, P., Haan, M., Luiten, A., and B. Schouten. 2021. “Understanding willingness to share smartphone-sensor data.” Public Opinion Quarterly. DOI: https://doi.org/10.1093/poq/nfaa044.813097934025296
]Search in Google Scholar
[
Toepoel, V. and P. Lugtig. 2015. “Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices in Web Surveys.” Methods, Data, Analyses 9: 155–162. DOI: https://doi.org/10.12758/mda.2015.009.
]Search in Google Scholar
[
Toepoel, V. and P. Lugtig. 2018. “Modularization in an Era of Mobile Web: Investigating the Effects of Cutting a Survey into Smaller Pieces on Data Quality.” Social Science Computer Review. DOI: https://doi.org/10.1177/0894439318784882.
]Search in Google Scholar
[
Tourangeau, R., F.G. Conrad, and M.P. Couper. 2013. The Science of Web Surveys. Oxford, GB: Oxford University Press.10.1093/acprof:oso/9780199747047.001.0001
]Search in Google Scholar
[
Tresch, A., L. Lauener, L. Bernhard, and L. Scaperrotta. 2020. Selects: Panel Survey (waves 1–3) – 2019 [Dataset]. Distributed by FORS, Lausanne, 2020. www.selects.ch. DOI: https://doi.org/10.23662/FORS-DS-1184-1.
]Search in Google Scholar
[
VanderWeele, T.J. 2015. Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford, UK: Oxford University Press.10.1093/ije/dyw277637349827864406
]Search in Google Scholar
[
VanderWeele, T.J. 2016. “Mediation Analysis: A Practitioner’s Guide.” Annual Review of Public Health 37: 17–32. DOI: https://doi.org/0.1146/annurev-publhealth-032315-021402.10.1146/annurev-publhealth-032315-02140226653405
]Search in Google Scholar
[
Watson, N. and M. Wooden. 2009. ‘‘Identifying Factors Affecting Longitudinal Survey Response.’’ In Methodology of Longitudinal Surveys edited by P. Lynn: 157–182. Chichester, England: John Wiley.10.1002/9780470743874.ch10
]Search in Google Scholar
[
Wells, T., J.T. Bailey, and M.W Link. 2013. “Filling the Void: Gaining a Better Understanding of Tablet-Based Surveys.” Survey Practice 6: 1–9. DOI: https://doi.org/10.29115/sp-2013-0002.
]Search in Google Scholar
[
Wenz, A. 2021. “Do Distractions During Web Survey Completion Affect Data Quality? Findings from a Laboratory Experiment.” Social Science Computer Review 3: 148–161. DOI: https://doi.org/10.1177/0894439319851503.
]Search in Google Scholar
[
Wenz, A., A. Jäckle, and M.P. Couper. 2019. “Willingness to Use Mobile Technologies for Data Collection in a Probability Household Panel.” Survey Research Methods 13: 1–22. DOI: https://doi.org/10.18148/srm/2019.v13i1.7298.
]Search in Google Scholar
[
Yan, T., S. Fricker, S., and S. Tsai. 2019. “Response Burden: What Predicts It and Who is Burdened Out?” In Advances in Questionnaire Design, Development, Evaluation and Testing edited by P. Beatty, D. Collins, L. Kaye, J.L. Padilla, G. Willis, and A. Wilmot, 193-212. Hoboken, NJ: John Wiley & Sons. DOI: https://doi.org/10.1002/9781119263685.ch8.
]Search in Google Scholar