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Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context Cover

Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context

Open Access
|Dec 2020

References

  1. Abu-Nimeh, S., D. Nappa, X. Wang, and S. Nair. 2008. . “Bayesian Additive Regression Trees-Based Spam Detection for Enhanced Email Privacy.” 2008 Third International Conference on Availability, Reliability and Security, Barcelona, Spain, 4–7 March 2008 IEEE. Available at: https://ieeexplore.ieee.org/abstract/document/4529459 (accessed May 2020).10.1109/ARES.2008.136
  2. Axinn, W., C. Link, and R. Groves. 2011. “Responsive Survey Design, Demographic Data Collection, and Models of Demographic Behavior.” Demography 48(3): 1–23. DOI: https://doi.org/10.1007/s13524-011-0044-1.10.1007/s13524-011-0044-121706256
  3. Barber, J.S., Y. Kusunoki, and H.H. Gatny. 2011. “Design and Implementation of an Online Weekly Survey to Study Unintended Pregnancies: Preliminary Results.” Vienna Yearbook of Population Research 9: 327–334. DOI: https://doi.org/10.1553/populationyearbook2011s327.10.1553/populationyearbook2011s327329818822408644
  4. Biemer, P.P., de Leeuw, E.D., Eckman, S., Edwards, B., Kreuter, F., Lyberg, L., Tucker, C., and West, B.T. (Eds.). 2017. Total Survey Error in Practice. Hoboken, New Jersey: Wiley.10.1002/9781119041702
  5. Biemer, P.P., and D. Trewin. 1997. “A Review of Measurement Error Effects on the Analysis of Survey Data.” In Survey Measurement and Process Quality, edited by L. Lyberg, P. Biemer, M. Collins, E. de Leeuw, C. Dippo, N. Schwarz, and D. Trewin. (pp. 601–632). New York: Wiley.10.1002/9781118490013.ch27
  6. Burger, J., K. Perryck, and B. Schouten. 2017. “Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters.” Journal of Official Statistics 33(3): 687–708. DOI: https://doi.org/10.1515/jos-2017-0032.10.1515/jos-2017-0032
  7. Chipman, H.A., E.I. George, and R.E. McCulloch. 2010. “BART: Bayesian Additive Regression Trees.” The Annals of Applied Statistics 4(1): 266–298. DOI: https://doi.org/10.1214/09-AOAS285.10.1214/09-AOAS285
  8. Dorie, V., H. Chipman, R. McCulloch, A. Dadgar, R.C. Team, G.U. Draheim, M. Bosmans, C. Tournayre, M. Petch, and R. de Lucena Valle. 2019. “dbarts: Discrete Bayesian Additive Regression Trees Sampler.” Available at: https://CRAN.R-project.org/package=dbarts (accessed May 2020).
  9. Durrant, G.B., O. Maslovskaya, and W.F. Smith Peter. 2017. “Using Prior Wave Information and Paradata: Can They Help to Predict Response Outcomes and Call Sequence Length in a Longitudinal Study?” Journal of Official Statistics 33(3): 801–833. DOI: https://doi.org/10.1515/jos-2017-0037.10.1515/jos-2017-0037
  10. Finamore, J., S. Coffey, and B. Reist. 2013. “National Survey of College Graduates: A Practice-Based Investigation of Adaptive Design.” Annual AAPOR Conference, May 16–19, 2013. Boston, MA, U.S.A.
  11. Green, D.P., and H.L. Kern. 2012. “Modeling Heterogeneous Treatment Effects in Survey Experiments with Bayesian Additive Regression Trees.” Public Opinion Quarterly 76(3): 491–511. DOI: https://doi.org/10.1093/poq/nfs036.10.1093/poq/nfs036
  12. Groves, R.M. 2006. “Nonresponse Rates and Nonresponse Bias in Household Surveys.” Public Opinion Quarterly 70(5): 646–675. DOI: https://doi.org/10.1093/poq/nfl033.10.1093/poq/nfl033
  13. Groves, R.M., and S.G. Heeringa. 2006. “Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 169(3): 439–457. DOI: https://doi.org/10.1111/j.1467-985X.2006.00423.x.10.1111/j.1467-985X.2006.00423.x
  14. Kern, C., T. Klausch, and F. Kreuter. 2019. “Tree-Based Machine Learning Methods for Survey Research.” Survey Research Methods 13(1): 73–93. DOI: https://doi.org/10.18148/srm/2019.v1i1.7395.
  15. Kirgis, N., and J. Lepkowski. 2013. “Design and Management Strategies for Paradata-Driven Responsive Design: Illustrations from the 2006-2010 National Survey of Family Growth.” In Improving Surveys with Paradata: Analytic Uses of Process Information, edited by F. Kreuter: 121–144. Hoboken, NJ: Wiley.10.1002/9781118596869.ch6
  16. Kleven, Ø., J. Fosen, B. Lagerstrøm, and L.-C. Zhang. 2010. . “The Use of R-Indicators in Responsive Survey Design–Some Norwegian Experiences.” Q2010 Conference, Helsinki, 3–6 May 2010. Available at: http://hummedia.manchester.ac.uk/institutes/cmist/risq/kleven-2010b.pdf (accessed May 2020)
  17. Laflamme, F., and M. Karaganis. 2010. “Implementation of Responsive Collection Design for CATI Surveys at Statistics Canada.” Proceedings of the European Conference on Quality in Official Statistics, Helsinki, Finland, Helsinki, Finland, 3–6 May, 2010. Available at: https://q2010.stat.fi/media/presentations/1_Responsive_design_paper_london_event1_revised.doc.
  18. Lewis, T. 2017. “Univariate Tests for Phase Capacity: Tools for Identifying When to Modify a Survey’s Data Collection Protocol.” Journal of Official Statistics 33(3): 601–624. DOI: https://doi.org/10.1515/jos-2017-0029.10.1515/jos-2017-0029
  19. Luiten, A., and B. Schouten. 2013. “Tailored Fieldwork Design to Increase Representative Household Survey Response: An Experiment in the Survey of Consumer Satisfaction.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 176(1): 169–189. DOI: https://doi.org/10.1111/j.1467-985X.2012.01080.x.10.1111/j.1467-985X.2012.01080.x
  20. Lundquist, P., and C.-E. Särndal. 2013. “Aspects of Responsive Design with Applications to the Swedish Living Conditions Survey.” Journal of Official Statistics 29(4): 557–582. DOI: https://doi.org/10.2478/jos-2013-0040.10.2478/jos-2013-0040
  21. Lynn, p. 2016. “Targeted Appeals for Participation in Letters to Panel Survey Members.” Public Opinion Quarterly 80(3): 771–782. DOI: https://doi.org/10.1093/poq/nfw024.10.1093/poq/nfw024
  22. Mohl, C., and F. Laflamme. 2007. “Research and Responsive Design Options for Survey Data Collection at Statistics Canada.” Joint Statistical Meetings, Salt Lake City, UT, 29 July–2 August, 2007. Available at: http://www.asasrms.org/Proceedings/y2007/Files/JSM2007-000421.pdf (accessed May 2020).
  23. Paiva, T., and J.P. Reiter. 2017. “Stop or Continue Data Collection: A Nonignorable Missing Data Approach for Continuous Variables.” Journal of Official Statistics 33(3): 579–599. DOI: https://doi.org/10.1515/jos-2017-0028.10.1515/jos-2017-0028
  24. Peytchev, A., R.K. Baxter, and L.R. Carley-Baxter. 2009. “Not All Survey Effort Is Equal: Reduction of Nonresponse Bias and Nonresponse Error.” Public Opinion Quarterly 73(4): 785–806. DOI: https://doi.org/10.1093/poq/nfp037.10.1093/poq/nfp037
  25. Peytchev, A., E. Peytcheva, and R.M. Groves. 2010. “Measurement Error, Unit Nonresponse, and Self-Reports of Abortion Experiences.” Public Opinion Quarterly 74(2): 319–327. DOI: https://doi.org/10.1093/poq/nfq002.10.1093/poq/nfq002
  26. Plewis, I., and N. Shlomo. 2017. “Using Response Propensity Models to Improve the Quality of Response Data in Longitudinal Studies.” Journal of Official Statistics 33(3): 753–779. DOI: https://doi.org/10.1515/jos-2017-0035.10.1515/jos-2017-0035
  27. Rao, R.S., M.E. Glickman, and R.J. Glynn. 2008. “Stopping Rules for Surveys with Multiple Waves of Nonrespondent Follow-Up.” Statistics in Medicine 27(12): 2196–2213. DOI: https://doi.org/10.1002/sim.3063.10.1002/sim.306317886234
  28. Rosen, J.A., J. Murphy, A. Peytchev, T. Holder, J. Dever, D. Herget, and D. Pratt. 2014. “Prioritizing Low Propensity Sample Members in a Survey: Implications for Nonresponse Bias.” Survey Practice 7(1). DOI: https://doi.org/10.1.1.686.6795.10.29115/SP-2014-0001
  29. Schonlau, M,. and M.P. Couper. 2016. “Semi-Automated Categorization of Open-Ended Questions.” Survey Research Methods 10(2): 143–152. DOI: https://doi.org/10.18148/srm/2016.v10i2.6213.
  30. Sparapani, R.A., B.R. Logan, R.E. McCulloch, and P.W. Laud. 2016. “Nonparametric Survival Analysis Using Bayesian Additive Regression Trees (BART).” Statistics in Medicine 35(16): 2741–2753. https://doi.org/DOI:10.1002/sim.6893.10.1002/sim.6893489927226854022
  31. Tabuchi, T., F. Laflamme, O. Phillips, M. Karaganis, and A. Villeneuve. 2009. “Responsive Design for the Survey of Labour and Income Dynamics.” Statistics Canada Symposium. October 27–30, 2009. Gatineau, Québec, Canada. Available at: http://oaresource.library.carleton.ca/wcl/2016/20160811/CS11-522-2009-eng.pdf#page=149.
  32. Tan, Y.V., C.A. Flannagan, and M.R. Elliott. 2018. “Predicting Human-Driving Behavior to Help Driverless Vehicles Drive: Random Intercept Bayesian Additive Regression Trees.” Statistics and Its Interface 11(4): 557–572. DOI: https://doi.org/10.4310/-SII.2018.v11.n4.a1.10.4310/SII.2018.v11.n4.a1
  33. Tourangeau, R., J. Michael Brick, S. Lohr, and J. Li. 2017. “Adaptive and Responsive Survey Designs: A Review and Assessment.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 180(1): 203–223. DOI: https://doi.org/10.1111/rssa.12186.10.1111/rssa.12186
  34. Wagner, J. 2019. “Estimation of Survey Cost Parameters Using Paradata.” Survey Practice 12(1): 1–10. DOI: https://doi.org/10.29115/SP-2018-003610.29115/SP-2018-0036
  35. Wagner, J., and K. Olson. 2018. “An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys.” Journal of Official Statistics 34(1): 211–237. DOI: https://doi.org/10.1515/jos-2018-0010.10.1515/jos-2018-0010
  36. Wagner, J., and T.E. Raghunathan. 2010. “A New Stopping Rule for Surveys.” Statistics in Medicine 29(9): 1014–1024. DOI: https://doi.org/10.1002/sim.3834.10.1002/sim.383420131311
  37. Wagner, J., B.T. West, H. Guyer, P. Burton, J. Kelley, M.P. Couper, and W.D. Mosher. 2017. “The Effects of a Mid-Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Family Growth.” In Total Survey Error in Practice, edited by P.P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L.E. Lyberg, N.C. Tucker, and B.T. West. New York. Wiley.10.1002/9781119041702.ch8
  38. West, B.T., and A.G. Blom. 2017. “Explaining Interviewer Effects: A Research Synthesis.” Journal of Survey Statistics and Methodology 5(2): 175–211. DOI: https://doi.org/10.1093/jssam/smw024.10.1093/jssam/smw024
  39. West, B.T., J. Wagner, F. Hubbard, and H. Gu. 2015. “The Utility of Alternative Commercial Data Sources for Survey Operations and Estimation: Evidence from the National Survey of Family Growth.” Journal of Survey Statistics and Methodology 3(2): 240–264. DOI: https://doi.org/10.1093/jssam/smv004.10.1093/jssam/smv004
  40. West, B.T., J. Wagner, S. Coffey, and M.R. Elliott. 2019. “The Elicitation of Prior Distributions for Bayesian Responsive Survey Design.” Historical Data Analysis versus Literature Review. Available at: https://arxiv.org/ftp/arxiv/papers/1907/1907.06560.pdf.
Language: English
Page range: 907 - 931
Submitted on: Aug 1, 2019
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Accepted on: May 1, 2020
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Published on: Dec 10, 2020
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 James Wagner, Brady T. West, Michael R. Elliott, Stephanie Coffey, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.