Literature DB >> 29606918

Optimizing Call Patterns for Landline and Cell Phone Surveys.

Becky Reimer1, Veronica Roth1, Robert Montgomery1.   

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.

Keywords:  National Flu Surveys; call patterns; calling rules; cell phone surveys; landline surveys; logistic regression

Year:  2012        PMID: 29606918      PMCID: PMC5875189     

Source DB:  PubMed          Journal:  Proc Am Stat Assoc        ISSN: 1543-3218


  2 in total

1.  What Factors Are Associated With Response Rates for Long-term Follow-up Questionnaire Studies in Hand Surgery?

Authors:  Ritsaart F Westenberg; Juliette Nierich; Jonathan Lans; Rohit Garg; Kyle R Eberlin; Neal C Chen
Journal:  Clin Orthop Relat Res       Date:  2020-12       Impact factor: 4.755

2.  Comparison response patterns on landline and cell phone in a call back survey: effects of demographic characteristics and lag days.

Authors:  Xiaoting Qin; Cathy M Bailey; Hatice S Zahran
Journal:  Surv Methods Insights Field       Date:  2019-05-17
  2 in total

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