[Allaire, J.J., J. Horner, Y. Xie, V. Marti, and N. Porte. 2019. markdown: Render Markdown with the C Library ’Sundown’. R package version 1.1. Available at: https://CRAN.R-project.org/package=markdown (accessed November 2020).]Search in Google Scholar
[Angel, S., R. Heuberger, and N. Lamei. 2017. “Differences Between Household Income from Surveys and Registers and How These Affect the Poverty Headcount: Evidence from the Austrian SILC.” Social Indicators Research, 138(2):575–603. DOI: https://doi.org/10.1007/s11205-017-1672-7.10.1007/s11205-017-1672-7601510329983479]Search in Google Scholar
[Bach, R.L. 2021. “A Methodological Framework for the Analysis of Panel Conditioning Effects.” In Measurement Error in Longitudinal Data. In Measurement Error in Longitudinal Data, edited by A. Cernat and J. Sakshaug. Oxford University Press, Oxford, UK: 19–41.]Search in Google Scholar
[Bach, R.L., and S. Eckman. 2018. “Motivated Misreporting in Web Panels.” Journal of Survey Statistics and Methodology, 6(3):418–430. DOI: https://doi.org/10.1093/jssam/smx030.10.1093/jssam/smx030]Search in Google Scholar
[Bach, R.L., and S. Eckman. 2019. “Participating in a Panel Survey Changes Respondents’ Labour Market Behaviour.” Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(1):263–281. DOI: https://doi.org/10.1111/rssa.12367.10.1111/rssa.12367]Search in Google Scholar
[Bach, R., and S. Eckman. 2020. “Rotation Group Bias in Reporting of Household Purchases in the U.S. Consumer Expenditure Survey.” Economics Letters. DOI: https://doi.org/10.1016/j.econlet.2019.108889.10.1016/j.econlet.2019.108889]Search in Google Scholar
[Bach, R.L., S. Eckman, and J. Daikeler. 2020. “Misreporting Among Reluctant Respondents.” Journal of Survey Statistics and Methodology, 8(3):566–588. DOI: https://doi.org/10.1093/jssam/smz013.10.1093/jssam/smz013]Search in Google Scholar
[Bailar, B.A. 1975. “The Effects of Rotation Group Bias on Estimates from Panel Surveys.” Journal of the American Statistical Association, 70(349):23. DOI: https://doi.org/10.2307/2285370.10.2307/2285370]Search in Google Scholar
[Bee, A., B.D. Meyer, and J.X. Sullivan. 2015. “The Validity of Consumption Data. Are the Consumer Expenditure Interview and Diary Surveys Informative?” In Improving the Measurement of Consumer Expenditures, edited by C.D. Carroll, T.F. Crossley, and J. Sabelhaus: 204–240. University of Chicago Press, Chicago.10.7208/chicago/9780226194714.003.0008]Search in Google Scholar
[Bosley, J.M. Dashen, and J. Fox. 1999. “When Should We Ask Follow-up Questions About Items in Lists?” In Proceedings of the Section on Survey Research Methods, American Statistical Association. Available at. http://www.asasrms.org/Proceedings/papers/1999_131.pdf (accessed November 2020).]Search in Google Scholar
[Cohen, S.B., and V.L. Burt. 1985. “Data Collection Frequency Effect in the National Medical Care Expenditure Survey.” Journal of Economic and Social Measurement, 13(2):125–151.]Search in Google Scholar
[Daikeler, J., R.L. Bach, H. Silber, and S. Eckman. 2020. “Motivated Misreporting in Smartphone Surveys.” Social Science Computer Review. DOI: https://doi.org/10.1177/0894439319900936.10.1177/0894439319900936]Search in Google Scholar
[Duan, N., M. Alegria, G. Canino, T. McGuire, and D. Takeuchi. 2007. “Survey Conditioning in Self-Reported Mental Health Service Use: Randomized Comparison of Alternative Instrument Formats.” Health Research and Educational Trust, 42(2):890–907. DOI: https://doi.org/10.1111/j.1475-6773.2006.00618.x.10.1111/j.1475-6773.2006.00618.x195535017362223]Search in Google Scholar
[Eckman, S. 2020. “Underreporting of Purchases in the U.S. Consumer Expenditure Survey.” Available at: https://osf.io/e3sgz/ (accessed November 2020).10.1093/jssam/smab024]Search in Google Scholar
[Eckman, S., and F. Kreuter. 2018. “Misreporting to Looping Questions in Surveys: Recall, Motivation and Burden.” Survey Research Methods, 12(1):59–74. DOI: https://doi.org/10.18148/srm/2018.v12i1.7168.]Search in Google Scholar
[Eckman, S., F. Kreuter, A. Kirchner, A. Jäckle, R. Tourangeau, and S. Presser. 2014. “Assessing the Mechanisms of Misreporting to Filter Questions in Surveys.” Public Opinion Quarterly, 78(3):721–733. DOI: https://doi.org/10.1093/poq/nfu030.10.1093/poq/nfu030]Search in Google Scholar
[Edgar, J. 2010. “Respondent Record Use in U.S. Consumer Expenditure Survey.” In Presented at the American Association for Public Opinion Research Conference, May 13–16, 2010, Chicago, Illinois, U.S.A. Available at: https://www.bls.gov/cex/research_papers/pdf/Respondent-Record-Use-in-the-US-Consumer-Expenditure-Survey-Presentation.pdf (accessed November 2020).]Search in Google Scholar
[Edgar, J., and J. Gonzalez. 2009. “Correlates of Data Quality in the Consumer Expenditure Quarterly Interview Survey.” In Proceedings of the Survey Research Methods Section of the American Statistical Association August 1–6, 2009, Washington D.C., U.S.A. Available at: https://www.bls.gov/osmr/research-papers/2009/pdf/st090140.pdf (accessed November 2020).]Search in Google Scholar
[Fricker, S, B. Kopp, L. Tan, and R. Tourangeau. 2015. “A Review of Measurement Error Assessment in a U.S. Household Consumer Expenditure Survey.” Journal of Survey Statistics and Methodology, 3(1):67–88. DOI: https://doi.org/10.1093/jssam/smu025.10.1093/jssam/smu025]Search in Google Scholar
[Halpern-Manners, A., and J.R. Warren. 2012. “Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey.” Demography, 49(4):1499–1519. DOI: https://doi.org/10.1007/s13524-012-0124-x.10.1007/s13524-012-0124-x364865922893185]Search in Google Scholar
[Halpern-Manners, A., J.R. Warren, and F. Torche. 2016. “Panel Conditioning in the General Social Survey.” Sociological Methods and Research, 46(1): 103–124. DOI: https://doi.org/10.1177/0049124114532445.10.1177/0049124114532445518185328025587]Search in Google Scholar
[Hansen, M.H., W.N. Hurwitz, H. Nisselson, and J. Steinberg. 1955. “The Redesign of the Census Current Population Survey.” Journal of the American Statistical Association, 50(271):701–719. DOI: https://doi.org/10.2307/2281161.10.2307/2281161]Search in Google Scholar
[Harrell Jr, F.E. 2020. with contributions from C. Dupont, and many others. Hmisc: Harrell Miscellaneous. R package version 4.4-1. Available at: https://CRAN.R-project.org/package=Hmisc (accessed November 2020).]Search in Google Scholar
[Hirsch, B.T., and J.V. Winters. 2016. “Rotation Group Bias in Measures of Multiple Job Holding.” Economic Letters, 147:160–163. DOI: https://doi.org/10.1016/j.econlet.2016.08.039.10.1016/j.econlet.2016.08.039]Search in Google Scholar
[Huntington-Klein, N. 2020. vtable: Variable Table for Variable Documentation. R package version 1.2.1. Available at: https://CRAN.R-project.org/package=vtable (accessed November 2020).]Search in Google Scholar
[Jensen, P.S., H.K. Watanabe, and J.E. Richters. 1999. “Who’s Up First? Testing for Order Effects in Structured Interviews Using a Counterbalanced Experimental Design.” Journal of Abnormal Child Psychology, 27:439–445. DOI: https://doi.org/10.1023/A:1021927909027.10.1023/A:1021927909027]Search in Google Scholar
[Kessler, R.C., H.-U. Wittchen, J.M. Abelson, K. McGonagle, N. Schwarz, K.S. Kendler, B. Knäuper, and S. Zhao. 1998. “Methodological Studies of the Composite International Diagnostic Interview (CIDI) in the US National Comorbidity Survey (NCS).” International Journal of Methods in Psychiatric Research, 7(1):33–55. DOI: https://doi.org/10.1002/mpr.33.10.1002/mpr.33]Search in Google Scholar
[Kreuter, F., S. McCulloch, S. Presser, and R. Tourangeau. 2011. “The Effects of Asking Filter Questions in Interleafed versus Grouped Format.” Sociological Methods and Research, 40(88):88–104. DOI: https://doi.org/10.1177/0049124110392342.10.1177/0049124110392342]Search in Google Scholar
[Krueger, A.B., A. Mas, and X. Niu. 2017. “The Evolution of Rotation Group Bias: Will the Real Unemployment Rate Please Stand Up?” Review of Economics and Statistics, 99(2):258–264. DOI: https://doi.org/10.1162/REST_a_00630.10.1162/REST_a_00630]Search in Google Scholar
[Lehnen, R.G., and A.J. Reiss. 1978. “Response Effects in the National Crime Survey.” Victomology, 3:110–160.]Search in Google Scholar
[Little, R.J.A. 1988. “Missing-Data Adjustments in Large Surveys.” Journal of Business and Economic Statistics, 6(3):287. DOI: https://doi.org/10.2307/1391878.10.2307/1391878]Search in Google Scholar
[Long, J.A. 2020. jtools: Analysis and Presentation of Social Scientific Data. R package version 2.1.0. Available at: https://cran.r-project.org/package=jtools (accessed November 2020).]Search in Google Scholar
[Mathiowetz, N.A., and T.J. Lair. 1994. “Getting Better? Change or Error in the Measurement of Functional Limitations.” Journal of Economic and Social Measurement, 20(3):237–262. DOI: https://doi.org/10.3233/JEM-1994-20305.10.3233/JEM-1994-20305]Search in Google Scholar
[McBride, B. 2013. “Examining Changes in Filter Question (FQ) Reporting in the Consumer Expenditure Quarterly Interview Survey.” In Proceedings of the Survey Research Methods Section of the American Statistical Association. Boston, Massachusetts, U.S.A.: 4304–4316. Available at: http://www.asasrms.org/Proceedings/y2013/files/400269_500735.pdf (accessed November 2020).]Search in Google Scholar
[Nancarrow, C., and T. Cartwright. 2007. “Online access panels and tracking research: The conditioning issue.” International Journal of Market Research, 49(5):573–594. DOI: https://doi.org/10.1177/147078530704900505.10.1177/147078530704900505]Search in Google Scholar
[National Research Council. 2013. Measuring What We Spend: Toward a New Consumer Expenditure Survey. The National Academies Press, Washington, D.C.]Search in Google Scholar
[Neter, J., and J. Waksberg. 1964. “Conditioning effects from Repeated Household Interviews.” Journal of Marketing, 28(2):51–56. DOI: https://doi.org/10.1177/002224296402800211.10.1177/002224296402800211]Search in Google Scholar
[Parker, J.A., N.S. Souleles, and C.D. Carroll. 2014. “In benefits of panel data in consumer expenditure surveys.” In Improving the Measurement of Consumer Expenditures: 75–99. University of Chicago Press. DOI: https://doi.org/10.7208/chicago/9780226194714.003.0004.10.7208/chicago/9780226194714.003.0004]Search in Google Scholar
[R Core Team. 2020. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Available at: https://www.R-project.org/ (accessed November 2020).]Search in Google Scholar
[Schonlau, M., and V. Toepoel. 2015. “Straightlining in Web Survey Panels Over Time.” Survey Research Methods, 9(2):125–137. DOI: https://doi.org/10.18148/srm/2015.v9i2.6128.]Search in Google Scholar
[Shields, J., and N. To. 2005. “Learning To Say No: Conditioned Underreporting in an Expenditure Survey.” In Proceedings of the Survey Research Methods Section of the American Statistical Association. Available at: http://www.asasrms.org/Proceedings/y2005/files/JSM2005-000432.pdf (accessed November 2020).]Search in Google Scholar
[Silberstein, A.R. 1990. “First Wave Effects in the U.S. Consumer Expenditure Interview Survey.” Survey Methodology, 16(2):293–304.]Search in Google Scholar
[Silberstein, A.R., and C.A. Jacobs. 1989. “Symptoms of Repeated Interview Effects in the Consumer Interview Survey.” In Panel Surveys, edited by D. Kasprzyk, G.J. Duncan, G. Kalton, and M.P. Singh, 289–303. Wiley, New York.]Search in Google Scholar
[Solon, G. 1986. “Effects of Rotation Group Bias on Estimation of Unemployment.” Journal of Business and Economic Statistics, 4(1):105–109. DOI: https://doi.org/10.1080/07350015.1986.10509499.10.1080/07350015.1986.10509499]Search in Google Scholar
[Struminskaya, B. 2016. “Respondent Conditioning in Online Panel Surveys. Results of Two Field Experiments.” Social Science Computer Review, 34(1):95–115. DOI: https://doi.org/10.1177/0894439315574022.10.1177/0894439315574022]Search in Google Scholar
[Sun, H., R. Tourangeau, and S. Presser. 2018. “Panel Effects: Do the Reports of Panel Respondents Get Better or Worse over Time?” Journal of Survey Statistics and Methodology, 7(4):572–588. DOI: https://doi.org/10.1093/jssam/smy021.10.1093/jssam/smy021]Search in Google Scholar
[U.S. Bureau of Labor Statistics. 2016. Consumer Expenditures and Income: Handbook of Methods. Available at. https://www.bls.gov/opub/hom/cex/pdf/cex.pdf (accessed November 2020).]Search in Google Scholar
[U.S. Bureau of Labor Statistics. 2020. Household Survey Response Rates. Available at: https://www.bls.gov/osmr/response-rates/household-survey-response-rates.htm (accessed November 2020).]Search in Google Scholar
[Van Buuren, S., and K. Groothuis-Oudshoorn. 2011. “mice: Multivariate Imputation by Chained Equations in R.” Journal of Statistical Software, 45(3):1–67. DOI: https://doi.org/10.18637/jss.v045.i03.10.18637/jss.v045.i03]Search in Google Scholar
[Venables, W.N., and B.D. Ripley. 2002. Modern Applied Statistics with S. Springer, New York, fourth edition. Available at: http://www.stats.ox.ac.uk/pub/MASS4 (accessed November 2020).10.1007/978-0-387-21706-2]Search in Google Scholar
[Waring, E., M. Quinn, A. McNamara, E. Arino de la Rubia, H. Zhu, and S. Ellis. 2020. “skimr: Compact and Flexible Summaries of Data, 2020. R package version 2.1.2. Available at: https://CRAN.R-project.org/package=skimr (accessed November 2020).]Search in Google Scholar
[Waterton, J., and D. Lievesley. 1989. “Evidence of Conditioning Effects in the British Social Attitudes Panel.” In Panel Surveys, edited by D. Kasprzyk, G.J. Duncan, G. Kalton, and M.P. Singh, 319–339. Wiley, New York.]Search in Google Scholar
[Wickham, H., M. Averick, J. Bryan, W. Chang, L. D’Agostino McGowan, R. François, G. Grolemund, A. Hayes, L. Henry, J. Hester, M. Kuhn, T. Lin Pedersen, E. Miller, S. Milton Bache, K. Müller, J. Ooms, D. Robinson, D. Paige Seidel, V. Spinu, K. Takahashi, D. Vaughan, C. Wilke, K. Woo, and H. Yutani. 2019. “Welcome to the Tidyverse.” Journal of Open Source Software, 4(43): 1686. DOI: https://doi.org/10.21105/joss.01686.10.21105/joss.01686]Search in Google Scholar
[Wilson, T., and S. Abdirizak. 2017. “Statistical Examination of Rounding Tendencies in the Consumer Expenditure Interview Survey.” In Proceedings of the American Statistical Association July 29–August 3, 2017, Baltimore, Maryland, U.S.A. 894–907. Available at: https://www.bls.gov/osmr/research-papers/2017/pdf/st170160.pdf (accessed November 2020).]Search in Google Scholar
[Yan, T., and K. Copeland. 2010. “Panel Conditioning in the Consumer Expenditure Quarterly Interview Survey.” In Proceedings of the Survey Research Methods Section of the American Statistical Association, May 13–16, 2010, Chicago, Illinois, U.S.A. Available at: http://www.asasrms.org/Proceedings/y2010/Files/307812_59394.pdf (accessed November 2020).]Search in Google Scholar
[Yan, T., and S. Eckman. 2012. “Panel Conditioning: Change in True Value versus Change in Self-Report.” In Proceedings of the Survey Research Methods Section of the American Statistical Association, July 28–August 2, 2012, San Diego, California, U.S.A. Available at: http://www.asasrms.org/Proceedings/y2012/Files/306203_76099.pdf (accessed November 2020).]Search in Google Scholar