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Using paradata to predict best times of contact, conditioning on household and interviewer influences

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  • Gabriele B. Durrant
  • Julia D'Arrigo
  • Fiona Steele

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  • Gabriele B. Durrant & Julia D'Arrigo & Fiona Steele, 2011. "Using paradata to predict best times of contact, conditioning on household and interviewer influences," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 1029-1049, October.
  • Handle: RePEc:bla:jorssa:v:174:y:2011:i:4:p:1029-1049 DOI: j.1467-985X.2011.00715.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-985X.2011.00715.x
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    References listed on IDEAS

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    1. Tunali, Insan & Pritchett, Jonathan B, 1997. "Cox Regression with Alternative Concepts of Waiting Time: The New Orleans Yellow Fever Epidemic of 1853," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 1-25, Jan.-Feb..
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    Cited by:

    1. Mark Hanly & Paul Clarke & Fiona Steele, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 793-808, June.
    2. Ronald R. Rindfuss & Minja K. Choe & Noriko O. Tsuya & Larry L. Bumpass & Emi Tamaki, 2015. "Do low survey response rates bias results? Evidence from Japan," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(26), pages 797-828, March.
    3. Lagorio, Carlos, 2016. "Call and response: modelling longitudinal contact and cooperation using Wave 1 call records data," Understanding Society Working Paper Series 2016-01, Understanding Society at the Institute for Social and Economic Research.

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