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Celeste Stone, Leslie Scott, Danielle Battle and Patricia Maher

References Andresen, E.M., Renea Machuga, C., van Booven, M.E., Egel, J., Chibnall, J.T., and Tait, R.C. (2008). Effects and Costs of Tracing Strategies on Nonresponse Bias in a Survey of Workers With Low-Back Injury. Public Opinion Quarterly, 72, 40-54. DOI: http://www.dx.doi.org/10.1093/poq/nfm055 Anstey, K.J., Luszcz, M.A., Giles, L.C., and Andrews, G.R. (2001). Demographic, Health, Cognitive, and Sensory Variables as Predictors of Mortality in Very Old Adults. Psychology and Aging, 16, 3-11. DOI: http://www.dx.doi.org/10

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Annamaria Bianchi, Silvia Biffignandi and Peter Lynn

26: 132–139. Farrant, G. and C. O’Muircheartaigh. 1991. “Components of Nonresponse Bias in the British Election Surveys.” In Understanding Political Change , edited by A. Heath, J. Curtice, R. Jowell, S. Evans, J. Field, and S. Witherspoon, 235–249. London: Pergamon Press. Fong, B. and J. Williams. 2011. “British Crime Survey: Feasibility of Boosting Police Force Area (PFA) Sample Sizes Using Supplementary Recontact Surveys.” Report for the Home Office, TNS-BMRB, London. Gaia, A. 2014. “Does a Mixed-Mode Design Increase Panel Attrition? Evidence

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Matej Stuhec and Jordi Serra-Mestres

significant DDIs in real clinical practice. This trial was found to have an overall high risk of bias because of its methodology (open label non-comparative multicentre trial), and almost all categories (outcomes blinding) were a source of bias, except attrition and reporting bias. Selection, performance, and detecting biases were high, because this trial was not a double blind, randomized, controlled trial ( Table 1 ). Table 1 Presentation of risk of bias assessments for trials included in this systematic review. Low risk of bias (+), high risk of bias

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Leandro D’Aurizio and Giuseppina Papadia

References Afonso, L.M. 2015. “Correcting for Attrition in Panel Data Using Inverse Probability Weighting: An application To the EU15 Bank System.” Doctoral dissertation (Lisbon School of Economics and Management, Working Paper) . Available at: https://www.repository.utl.pt/bitstream/10400.5/8155/1/DM-LMA-2015.pdf (accessed January 2019). Ardilly, P. and P. Lavallée. 2007. “Weighting in Rotating Samples: The SILC survey in France.” Survey Methodology 33(2): 131–137. Bank of Italy. 2005. Supplements to the Statistical Bulletin, Sample

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Peter Wennberg, Johan Svensson and Mats Ramstedt

): Tracking and follow-up of 16,915 adolescents: Minimizing attrition bias. Controlled Clinical Trials 18: 383-396 Pope, D. & Croft, P. (1996): Surveys using general practice registers: who are the non-responders? Journal of Public Health Medicine 18: 6-12 Ramstedt, M. (2010): How much alcohol do you buy? A comparison of self-reported alcohol purchases with actual sales. Addiction 105: 649-654 Thygesen, L. C. & Johansen, C. & Keiding, N. & Giovannucci, E. & Gronbaek, M. (2008): Effects of sample

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Bart Buelens and Jan A. Van den Brakel

. “Response strategies for Coping with the Cognitive Demands of Attitude Measures in Surveys.” Applied Cognitive Psychology 5: 213–236. Doi: http://dx.doi.org/10.1002/acp.2350050305 . Krosnick, J. and D. Alwin. 1987. “An Evaluation of a Cognitive Theory of Response-Order Effects in Survey Measurement.” Public Opinion Quarterly 51: 201–219. Doi: http://dx.doi.org/10.1086/269029 . Lynn, P. 2013. “Alternative Sequential Mixed-Mode Designs: Effects on Attrition Rates, Attrition Bias, and Costs.” Journal of Survey Statistics and Methodology 1(2): 183–205. Doi

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Ian Plewis and Natalie Shlomo

. Groves, R.M. 2006. “Nonresponse Rates and Non-response Bias in Household Surveys.” Public Opinion Quarterly 70: 646–675. Doi: http://dx.doi.org/10.1093/poq/nfl033 . Hawkes, D. and I. Plewis. 2006. “Modelling Non-Response in the National Child Development Study.” Journal of the Royal Statistical Society, Series A 169: 479–491. Doi: http://dx.doi.org/10.1111/j.1467-985X.2006.00401.x . Lynn, P., O. Kaminska, and H. Goldstein. 2014. “Panel Attrition: How Important is Interviewer Continuity?” Journal of Official Statistics 30: 443–457. Doi: http

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Caroline Roberts and Caroline Vandenplas

Official Statistics 22: 293–312. Lipps, O., N. Pekari, and C. Roberts. 2015. “Undercoverage and Nonresponse in a List-Sampled Telephone Election Study.” Survey Research Methods 9(2): 71–82. Doi: http://dx.doi.org/10.18148/srm/2015.v9i2.6139 . Lynn, P. 2013. “Alternative Sequential Mixed-Mode Designs: Effects on Attrition Rates, Attrition Bias, and Costs.” Journal of Survey Statistics and Methodology 1: 183–205. Doi: http://dx.doi.org/10.1093/jssam/smt015 . Massey, D.S. and R. Tourangeau. 2013. “Where Do We Go from Here? Nonresponse and Social

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Olena Kaminska and Peter Lynn

. Uhrig, S.C. 2008. The Nature and Causes of Attrition in the British Household Panel Study. ISER Working Paper Series , 2008(05). Colchester: Institute for Social and Economic Research, University of Essex. Wagner, J.R. 2008. Adaptive Survey Design to Reduce Nonresponse Bias , PhD Dissertation. University of Michigan. Wagner, J.R. 2012. “Research Synthesis: a Comparison of Alternative Indicators for the Risk of Nonresponse Bias.” Public Opinion Quarterly 76(3): 555–575. Doi: http://dx.doi.org/10.1093/poq/nfs032 . Watson, N. and M. Wooden. 2009

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J. Michael Brick

References Andridge, R.H. and Little, R.J. (2011). Proxy Pattern-Mixture Analysis for Survey Nonresponse. Journal of Official Statistics, 27, 153-180. Atrostic, B.K., Bates, N., Burt, G., and Silberstein, A. (2001). Nonresponse in U.S. Government Household Surveys: Consistent Measures, Recent Trends, and New Insights. Journal of Official Statistics, 17, 209-226. Bartholomew, D.J. (1961). A Method of Allowing for ‘Not-at-Home’ Bias in Sample Surveys. Applied Statistics, 10, 52-59. Bates, N