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在混合设备调查设计中使用模式切换最大化数据质量:无应答偏差与人口行为模型

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

作者信息

Axinn William G, Gatny Heather H, Wagner James

机构信息

University of Michigan Survey Research Center.

出版信息

Methoden Daten Anal. 2015;9(2):163-184. doi: 10.12758/mda.2015.010.

DOI:10.12758/mda.2015.010
PMID:26865882
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4746010/
Abstract

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.

摘要

在互联网上进行调查访谈已成为一种颇具吸引力的方法,可降低数据收集成本并提高访谈频率,尤其是在纵向研究中。然而,网络模式在频繁重新访谈研究中的优势可能会被低回应率这一严重劣势以及无回应偏差误导研究者的可能性所抵消。重要的生活事件,如就业状况变化、关系变化或搬家等,可能导致纵向研究出现人员流失,产生人员流失偏差的可能性。纵向网络调查中此类偏差的潜在程度尚未得到充分了解。我们使用来自关系动态与社会生活(RDSL)研究的数据,来检验采用主动模式切换的混合设备方法减少人员流失偏差的可能性。RDSL设计允许小组成员通过将电话访谈纳入纵向网络调查来切换模式,目的是收集每周报告。我们发现,在这种设计中,与仅采用网络模式的方法相比,允许小组成员切换模式能使更多参与者留在研究中。曾经切换模式的人与未切换模式的人在特征上有所不同——不仅包括人口统计学特征,还包括与怀孕相关的基线特征以及在基线访谈后收集的随时间变化的特征。在同时控制多个这些维度的多变量模型中也是如此。我们得出结论,模式选择和模式切换对于纵向网络调查的成功至关重要,可最大限度地提高参与度并最小化人员流失。

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