RSD Bibliography

Almirall, D., Compton, S.N, Rynn, M.A., Walkup, J.T., and Murphy, S.A. (2012a). SMARTer discontinuation trials: With application to the treatment of anxious youth. Journal of Child and Adolescent Psychopharmacology, 22(5), 364-374.

Almirall, D., Lizotte, D., and Murphy, S.A. (2012b). SMART design issues and the consideration of opposing outcomes: A discussion of “Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer” by Wang, Rotnitzky, Lin, Millikan, and Thall. Journal of the American Statistical Association (Case Studies and Applications), 107(498), 509-512.

Axinn, W.G., Link, C.F., and Groves, R.M. (2011). Responsive survey design, demographic data collection, and models of demographic behavior. Demography, 48, 1127-1149.

Barber, J.S., Kusunoki, Y., and Gatny, H.H. (2011). Design and implementation of an online weekly survey to study unintended pregnancies. Vienna Yearbook of Population Research, 9, 327-334. PMCID: PMC3298188.

Berkel, K. van, Doef, S. van der, Schoutenb, B. van. (2020). Implementing Adaptive Survey Design With an Application to the Dutch Health Survey. Journal of Official Statistics, 36(3), 609–629.

Brick, J. & Tourangeau, R. (2017). Responsive Survey Designs for Reducing Nonresponse Bias. Journal of Official Statistics, 33(3), pp. 735-752. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0034.

Burger, J., Perryck, K. & Schouten, B. (2017). Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters. Journal of Official Statistics, 33(3), pp. 687-708. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0032.

Calinescu, M., Bhulai, S., and Schouten, B. (2013). Optimal resource allocation in survey designs. European Journal of Operational Research, 226(1), 115-121.

Carpenter, H., & Burton, J. (2018). Adaptive push-to-web: experiments in a household panel study (No. 2018-05). Understanding Society at the Institute for Social and Economic Research.

Chow, S.C. and Chang, M. (2008). Adaptive design methods in clinical trials – A review. Orphanet Journal of Rare Diseases, 3(11). 169-190.

Chun, A., Heeringa, S. & Schouten, B. (2018). Responsive and Adaptive Design for Survey Optimization. Journal of Official Statistics, 34(3), pp. 581-597. Retrieved 4 Sep. 2018, from doi:10.2478/jos-2018-0028.

Chun, A., Schouten, B. & Wagner, J. (2017). JOS Special Issue on Responsive and Adaptive Survey Design: Looking Back to See Forward – Editorial. Journal of Official Statistics, 33(3), pp. 571-577. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0027.

Couper, M.P., Peytchev, A., Strecher, V.J., Rothert, K., and Anderson, J. (2007). Following up nonrespondents to an online weight management intervention: Randomized trial comparing mail versus telephone. Journal of Medical Internet Research 9(2), e16.

Durrant, G.B., D'Arrigo, J., and Steele, F. (2011). Using field process data to predict best times of contact conditioning on household and interviewer influences. Journal of the Royal Statistical Society Series A (Statistics in Society), 174(4), 1029-1049.

Durrant, G., Maslovskaya, O. & Smith, P. (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), pp. 801-833. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0037.

Early, K., Mankoff, J. & Fienberg, S. (2017). Dynamic Question Ordering in Online Surveys. Journal of Official Statistics, 33(3), pp. 625-657. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0030.

Groves, R.M. and Heeringa, S.G. (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.

Gummer, T., & Blumenstiel, J. E. (2018). Experimental Evidence on Reducing Nonresponse Bias through Case Prioritization: The Allocation of Interviewers. Field Methods, 1525822X18757967.

Hansen, M.H. and Hurwitz, W.N. (1946). The problem of nonresponse in sample surveys. Journal of the American Statistical Society, 41(236), 517-529.

Jackson, M. T., Mcphee, C. B., & Lavrakas, P. J. (2019). Using Response Propensity Modeling to Allocate Noncontingent Incentives in An Address-Based Sample: Evidence from a National Experiment. Journal of Survey Statistics and Methodology.

Kaminski, B., M. Kozakiewicz, W. Jakuczun and M. Poltorak (2012). An optimal assignment procedure for multiple online surveys. Operations Research and Decisions, 22(4), 69-85.

Kaminska, O. & Lynn, P. (2017). The Implications of Alternative Allocation Criteria in Adaptive Design for Panel Surveys. Journal of Official Statistics, 33(3), pp. 781-799. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0036.

Kappelhof, J. W., & De Leeuw, E. D. (2017). Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response among Non-Western Minorities. Sociological Methods & Research, 0049124117701474.

Kaputa, S. J., Thompson, K. J., & Beck, J. L. (2019). An embedded experiment for targeted non-response follow-up in establishment surveys. Journal of the Royal Statistical Society: Series A (Statistics in Society).

Kirgis, N.G. and Lepkowski, J.M. (2013). Design and management strategies for paradata-driven responsive design: Illustrations from the 2006-2010 National Survey of Family Growth. Chapter 6 in Improving Surveys with Paradata: Analytic Uses of Process Information. Hoboken: Wiley.

Kreuter, F. (Editor) (2013). Improving surveys with paradata: Analytic uses of process information. Hoboken: Wiley.

Lavrakas, P.L., Jackson, M., & McPhee, C. (2018). The Use of Response Propensity Modeling (RPM) for Allocating Differential Survey Recruitment Strategies: Purpose, Rationale, and Implementation. Survey Practice, 11(2), 3705.

Lei H., Nahum-Shani, I., Lynch, K., Oslin, D., and Murphy, S.A. (2012). A "SMART" design for building individualized treatment sequences. Annual Review of Clinical Psychology, 8, 21-48.

Lepkowski, J.M., Mosher, W.D., Groves, R.M., West, B.T., Wagner, J., and Gu, H. (2013). Responsive design, weighting, and variance estimation in the 2006-2010 National Survey of Family Growth. Vital and Health Statistics, 2(158). National Center for Health Statistics.

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), pp. 601-624. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0029.

Lewis, T., Gorsak, M., & Yount, N. (2019). An Automated Refusal Conversion Strategy for Web Surveys. Field Methods, 31(4), 309–327.

Luiten, A. and Schouten, B. (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.

Lundquist, P. and Särndal, C.E. (2011). Aspects of responsive design for the Swedish Living Conditions Survey. Research and Development: Methodology Reports from Statistics Sweden. Statistics Sweden.

Lynn, P. (2017). From standardised to targeted survey procedures for tackling non-response and attrition. Survey Research Methods, 11(1), 93-103. doi:

McCarthy, J., Wagner, J. & Sanders, H. (2017). The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design. Journal of Official Statistics, 33(3), pp. 857-871. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0039.

Mohl, C. and Laflamme, F. (2007). Research and responsive design options for survey data collection at Statistics Canada. In JSM Proceedings (Section on Survey Research Methods), 2962-2968.

Murphy S.A. (2003). Optimal dynamic treatment regimes. Journal of the Royal Statistical Society Series B (Statistical Methodology), 65(2), 331-355.

Murphy, S.A. (2005). An experimental design for the development of adaptive treatment strategies. Statistics in Medicine, 24(10), 1455–1481.

Murphy, S.A. and Almirall, D. (2009). Dynamic treatment regimens. In M.W. Kattan (Ed.), Encyclopedia of Medical Decision Making. Thousand Oaks: Sage Publications.

Murphy, J., Biemer, P. & Berry, C. (2018). Transitioning a Survey to Self-Administration using Adaptive, Responsive, and Tailored (ART) Design Principles and Data Visualization. Journal of Official Statistics, 34(3), pp. 625-648. Retrieved 4 Sep. 2018, from doi:10.2478/jos-2018-0030.

Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W., Gnagy, B., Fabiano, G., Waxmonsky, J., Yu, J., Murphy, S.A. (2013). Experimental design and primary data analysis methods for comparing adaptive interventions. Psychological Methods, 17(4), 457-477.

Paiva, T. & Reiter, J. (2017). Stop or Continue Data Collection: A Nonignorable Missing Data Approach for Continuous Variables. Journal of Official Statistics, 33(3), pp. 579-599. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0028.

Peytchev, A. (2019). Split-Sample Design with Parallel Protocols to Reduce Cost and Nonresponse Bias in Surveys. Journal of Survey Statistics and Methodology, smz033.

Peytchev, A., Baxter, R.K., and Carley-Baxter, L.R. (2009). Not all survey effort is equal: Reduction of nonresponse bias and nonresponse error. Public Opinion Quarterly, 73(4), 785-806.

Peytchev, A., Pratt, D., Duprey, M. (2020). Responsive and Adaptive Survey Design: Use of Bias Propensity During Data Collection to Reduce Nonresponse Bias. Retrieved 31 Dec. 2020, from Peytchev, A., Riley, S., Rosen, J., Murphy, J. and Lindblad, M. (2010). Reduction of Nonresponse Bias in Surveys through Case Prioritization. Survey Research Methods, 4, 21-29.

Plewis, I. & Shlomo, N. (2017). Using Response Propensity Models to Improve the Quality of Response Data in Longitudinal Studies. Journal of Official Statistics, 33(3), pp. 753-779. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0035.

Rosen, J.A., J. Murphy, A. Peytchev, T. Holder, J.A. Dever, D.R. Herget and D.J. Pratt. 2014. Prioritizing Low-Propensity Sample Members in a Survey: Implications for Nonresponse Bias. Survey Practice. 7(1)

Sakshaug, J. W., Hülle, S., Schmucker, A., & Liebig, S. (2019). Panel Survey Recruitment With or Without Interviewers? Implications for Nonresponse, Panel Consent, and Total Recruitment Bias. Journal of Survey Statistics and Methodology.

Sampson, N. R., Webster, N. J., Nassauer, J. I., & Schulz, A. J. (2019). Adapting social surveys to depopulating neighborhoods. Landscape and Urban Planning, 181, 45-50.

Santin, G., Bénézet, L., Geoffroy-Perez, B., Bouyer, J., & Guéguen, A. (2017). A two-phase sampling survey for nonresponse and its paradata to correct nonresponse bias in a health surveillance survey. Revue d'Épidémiologie et de Santé Publique, 65(1), 71-79.

Särndal, C. & Lundquist, P. (2017). Inconsistent Regression and Nonresponse Bias: Exploring Their Relationship as a Function of Response Imbalance. Journal of Official Statistics, 33(3), pp. 709-734. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0033.

Sauermann, H. and Roach, M. (2013). Increasing web survey response rates in innovation research: An experimental study of static and dynamic contact design features. Research Policy, 42(1), 273-286.

Schouten, B., Bethlehem, J., Beullens, K., Kleven, Ø., Loosveldt, G., Luiten, A., Rutar, K., Shlomo, N., and Skinner, C. (2012). Evaluating, comparing, monitoring, and improving representativeness of survey response through R-indicators and partial R-indicators. International Statistical Review, 80(3), 382-399.

Schouten, B., Calinescu, M., and Luiten, A. (2011). Optimizing quality of response through adaptive survey designs. Discussion paper 201118, The Hague: Statistics Netherlands.

Schouten, B., F. Cobben and J. G. Bethlehem. (2009). Indicators for the representativeness of survey response. Survey Methodology, 35(1), 101-113.

Schouten, B., Cobben, F., Lundquist, P., & Wagner, J. (2016). Does more balanced survey response imply less non‐response bias?. Journal of the Royal Statistical Society: Series A (Statistics in Society), 179(3), 727-748.

Schouten, B., Mushkudiani, N., Shlomo, N., Durrant, G., Lundquist, P., & Wagner, J. (2018). A Bayesian analysis of design parameters in survey data collection. Journal of Survey Statistics and Methodology.

Smith, N. and J. Malley (2012). "Understanding and addressing underrepresentation in a postal survey of social care users." Online report published by Quality and Outcomes of Person-Centered Care Policy Research Unit at University of Kent. Dowloaded at on September 9, 2014.

Tabuchi, T., Laflamme, F., Phillips, O., Karaganis, M., and Villeneuve, A. (2009). Responsive design for the survey of labour and income dynamics. In Proceedings of Statistics Canada Symposium 2009. Statistics Canada.

Thompson, K. & Kaputa, S. (2017). Investigating Adaptive Nonresponse Follow-up Strategies for Small Businesses through Embedded Experiments. Journal of Official Statistics, 33(3), pp. 835-856. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0038.

Tourangeau, R., Brick, J.M., Lohr, S. and Li, J. (2016). Adaptive and responsive survey designs: a review and assessment. Journal of the Royal Statistical Society - Series A, 180(1), 203-223.

Vandenplas, C., Loosveldt, G. & Beullens, K. (2017). Fieldwork Monitoring for the European Social Survey: An illustration with Belgium and the Czech Republic in Round 7. Journal of Official Statistics, 33(3), pp. 659-686. Retrieved 12 Sep. 2017, from doi:10.1515/jos-2017-0031.

Wagner, J. (2008). Adaptive Survey Design to Reduce Nonresponse Bias. Program in Survey Methodology. Ann Arbor, University of Michigan. PhD Disseration.

Wagner, J., J. Arrieta, H. Guyer and M.B. Ofstedal. (2014). Does Sequence Matter in Multimode Surveys: Results from an Experiment. Field Methods, 26(2), 141-155.

Wagner, J., West, B.T., Kirgis, N., Lepkowski, J.M., Axinn, W.G., and Kruger-Ndiaye, S. (2012). Use of paradata in a responsive design framework to manage a field data collection. Journal of Official Statistics, 28(4), 477-499.