Optimizing Call Patterns for Landline and Cell Phone Surveys.

Becky Reimer, Veronica Roth, Robert Montgomery
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Abstract

Cell phone surveys have become increasingly popular and researchers have noted major challenges in conducting cost-effective surveys while achieving high response rates. Previous work has shown that calling strategies that maximize both respondent contact and completed interviews for landline surveys may not be the most cost-effective for cell phone surveys. For example, Montgomery, et al. (2011) found important differences between landline and cell samples for best times to call and declines in contact rates after repeated dialing. Using paradata from the 2010 and 2011 National Flu Surveys (sponsored by the Centers for Disease Control and Prevention), we investigate differences in calling outcomes between landline and cell surveys. Specifically, we predict respondent contact and interview completion using logistic regression models that examine the impact of calling on particular days of the week, certain times of the day, number of previous calls, outcomes of previous calls and length of time between calls. We discuss how these differences can be used to increase the likelihood of contacting cooperative respondents and completing interviews for both sample types.

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优化座机和手机调查的通话模式。
手机调查越来越受欢迎,研究人员注意到在实现高回复率的同时进行具有成本效益的调查的主要挑战。先前的研究表明,在固定电话调查中,最大化应答者接触和完成访谈的呼叫策略可能不是手机调查中最具成本效益的。例如,Montgomery等人(2011年)发现固定电话和手机样本在最佳通话时间和重复拨号后的接触率下降方面存在重要差异。使用2010年和2011年全国流感调查(由疾病控制和预防中心赞助)的数据,我们调查了固定电话和手机调查之间通话结果的差异。具体来说,我们使用逻辑回归模型来预测受访者的联系和访谈完成情况,该模型检查了在一周的特定日期,一天的特定时间,以前的电话数量,以前的电话结果和电话之间的时间长度呼叫的影响。我们讨论如何使用这些差异来增加联系合作受访者和完成两种样本类型访谈的可能性。
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