Doorstep Interactions and Interviewer Effects on the Process Leading to Cooperation or Refusal
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DOI: 10.1177/0049124114521148
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References listed on IDEAS
- Durrant, Gabriele B. & D'Arrigo, Julia & Steele, Fiona, 2011. "Using field process data to predict best times of contact conditioning on household and interviewer influences," LSE Research Online Documents on Economics 52201, London School of Economics and Political Science, LSE Library.
- Jan Pickery & Geert Loosveldt, 2002. "A Multilevel Multinomial Analysis of Interviewer Effects on Various Components of Unit Nonresponse," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(4), pages 427-437, November.
- Gabriele B. Durrant & Julia D'Arrigo & Fiona Steele, 2013. "Analysing interviewer call record data by using a multilevel discrete time event history modelling approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 251-269, January.
- 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.
- Brady T. West, 2013. "An examination of the quality and utility of interviewer observations in the National Survey of Family Growth," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 211-225, January.
- Cheti Nicoletti & Franco Peracchi, 2005. "Survey response and survey characteristics: microlevel evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 763-781, November.
- Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
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- Roger Tourangeau & J. Michael Brick & Sharon Lohr & Jane Li, 2017. "Adaptive and responsive survey designs: a review and assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 203-223, January.
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