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Maximizing Data Quality using Mode Switching in Mixed-Device Survey Design: Nonresponse Bias and Models of Demographic Behavior

Conducting survey interviews on the internet has become an attractive method for lowering data collection costs and increasing the frequency of interviewing, especially in longitudinal studies. However, the advantages of the web mode for studies with frequent re-interviews can be offset by the serio...

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Detalles Bibliográficos
Autores principales: Axinn, William G., Gatny, Heather H., Wagner, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746010/
https://www.ncbi.nlm.nih.gov/pubmed/26865882
http://dx.doi.org/10.12758/mda.2015.010
Descripción
Sumario:Conducting survey interviews on the internet has become an attractive method for lowering data collection costs and increasing the frequency of interviewing, especially in longitudinal studies. However, the advantages of the web mode for studies with frequent re-interviews can be offset by the serious disadvantage of low response rates and the potential for nonresponse bias to mislead investigators. Important life events, such as changes in employment status, relationship changes, or moving can cause attrition from longitudinal studies, producing the possibility of attrition bias. The potential extent of such bias in longitudinal web surveys is not well understood. We use data from the Relationship Dynamics and Social Life (RDSL) study to examine the potential for a mixed-device approach with active mode switching to reduce attrition bias. The RDSL design allows panel members to switch modes by integrating telephone interviewing into a longitudinal web survey with the objective of collecting weekly reports. We found that in this design allowing panel members to switch modes kept more participants in the study compared to a web only approach. The characteristics of persons who ever switched modes are different than those who did not – including not only demographic characteristics, but also baseline characteristics related to pregnancy and time-varying characteristics that were collected after the baseline interview. This was true in multivariate models that control for multiple of these dimensions simultaneously. We conclude that mode options and mode switching is important for the success of longitudinal web surveys to maximize participation and minimize attrition.