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Applied Economics Volume 49, 2017 - Issue 22
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Original Articles

A contribution on the nature and treatment of missing data in large market surveys

Gary MaddenDepartment of Economics and Property, Curtin University, Perth, AustraliaCorrespondence[email protected]
,
María Rosalía VicenteDepartment of Applied Economics, University of Oviedo, Oviedo, Spain
,
Paul RappoportDepartment of Economics, Temple University, Philadelphia, PA, USA
&
Andy BanerjeeCentris Market Intelligence, Boston, MA, USA
Pages 2179-2187 | Published online: 27 Oct 2016

References

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  • Bennett, D. 2001. “How Can I Deal with Missing Data in My Study?” Australian and New Zealand Journal of Public Health 25: 464–469. doi:10.1111/azph.2001.25.issue-5.
  • Buhi, E., P. Goodson, and T. Neilands. 2008. “Out of Sight, Not Out of Mind: Strategies for Handling Missing Data.” American Journal of Health Behavior 32: 83–92. doi:10.5993/AJHB.32.1.8.
  • Chen, H., and R. Little. 1999. “A Test of Missing Completely at Random for Generalised Estimating Equations with Missing Data.” Biometrika 86 (1): 1–13. doi:10.1093/biomet/86.1.1.
  • Graham, J. 2009. “Missing Data Analysis: Making It Work in the Real World.” Annual Review of Psychology 60: 549–576. doi:10.1146/annurev.psych.58.110405.085530.
  • Hair, J., W. Black, B. Babin, and R. Anderson. 2009. Multivariate Data Analysis. 7th ed. Upper Saddle River: Pearson.
  • Little, R. 1988a. “Missing-Data Adjustments in Large Surveys.” Journal of Business and Economic Statistics 6: 287–296.
  • Little, R. 1988b. “A Test of Missing Completely at Random for Multivariate Data with Missing Values.” Journal of the American Statistical Association 83: 1198–1202. doi:10.1080/01621459.1988.10478722.
  • Little, R., and D. Rubin. 2002. Statistical Analysis with Missing Data. 2nd ed. Hoboken: John Wiley and Sons.
  • OECD, European Commission, Joint Research Centre. 2008. Handbook on Constructing Composite Indicators: Methodology and User Guide. Paris: OECD.
  • Park, T., and C. Davis. 1993. “A Test of the Missing Data Mechanism for Repeated Categorical Data.” Biometrics 49 (2): 631-638. doi:10.2307/2532576.
  • Potthoff, R., G. Tudor, K. Pieper, and V. Hasselblad. 2006. “Can One Assess whether Missing Data are Missing at Random in Medical Studies?” Statistical Methods in Medical Research 15: 213–234. doi:10.1191/0962280206sm448oa.
  • Qu, A., and P. Song. 2002. “Testing Ignorable Missingness in Estimating Equation Approaches for longitudinal Data.” biometrika 89 (4): 841-850. doi:10.1093/biomet/89.4.841.
  • Rubin, D. 1987. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley and Sons.

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