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The Implications of Alternative Allocation Criteria in Adaptive Design for Panel Surveys

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  • Kaminska Olena
  • Lynn Peter

    (ISER, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom of Great Britain and Northern Ireland.)

Abstract

Adaptive survey designs can be used to allocate sample elements to alternative data collection protocols in order to achieve a desired balance between some quality measure and survey costs. We compare four alternative methods for allocating sample elements to one of two data collection protocols. The methods differ in terms of the quality measure that they aim to optimize: response rate, R-indicator, coefficient of variation of the participation propensities, or effective sample size. Costs are also compared for a range of sample sizes. The data collection protocols considered are CAPI single-mode and web-CAPI sequential mixed-mode. We use data from a large experiment with random allocation to one of these two protocols. For each allocation method we predict outcomes in terms of several quality measures and costs. Although allocating the whole sample to single-mode CAPI produces a higher response rate than allocating the whole sample to the mixed-mode protocol, we find that two of the targeted allocations achieve a better response rate than single-mode CAPI at a lower cost. We also find that all four of the targeted designs out-perform both single-protocol designs in terms of representativity and effective sample size. For all but the smallest sample sizes, the adaptive designs bring cost savings relative to CAPI-only, though these are fairly modest in magnitude.

Suggested Citation

  • Kaminska Olena & Lynn Peter, 2017. "The Implications of Alternative Allocation Criteria in Adaptive Design for Panel Surveys," Journal of Official Statistics, Sciendo, vol. 33(3), pages 781-799, September.
  • Handle: RePEc:vrs:offsta:v:33:y:2017:i:3:p:781-799:n:10
    DOI: 10.1515/jos-2017-0036
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    References listed on IDEAS

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    1. Auspurg, Katrin & Burton, Jonathan & Cullinane, Carl & Delavande, Adeline & Laura, Fumagalli & Iacovou, Maria & Jäckle, Annette & Kaminska, Olena & Lynn, Peter & Mathews, Paul & Nicolaas, Gerry & Nic, 2013. "Understanding Society Innovation Panel Wave 5: results from methodological experiments," Understanding Society Working Paper Series 2013-06, Understanding Society at the Institute for Social and Economic Research.
    2. Schouten, Barry & Shlomo, Natalie & Skinner, Chris J., 2011. "Indicators for monitoring and improving representativeness of response," LSE Research Online Documents on Economics 39121, London School of Economics and Political Science, LSE Library.
    3. 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.
    4. Barry Schouten & Jelke Bethlehem & Koen Beullens & Øyvin Kleven & Geert Loosveldt & Annemieke Luiten & Katja Rutar & Natalie Shlomo & Chris Skinner, 2012. "Evaluating, Comparing, Monitoring, and Improving Representativeness of Survey Response Through R-Indicators and Partial R-Indicators," International Statistical Review, International Statistical Institute, vol. 80(3), pages 382-399, December.
    5. Noah Uhrig, S.C., 2008. "The nature and causes of attrition in the British Household Panel Study," ISER Working Paper Series 2008-05, Institute for Social and Economic Research.
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    Cited by:

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    3. Peter Lynn & Pablo Cabrera‐Álvarez & Paul Clarke, 2023. "Sample composition and representativeness on Understanding Society," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 341-359, December.

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