Open Access

Detecting and Treating Verified Influential Values in a Monthly Retail Trade Survey


Cite

Barth, J., J. Tillinghast, and M.H. Mulry. 2012. “Treatment of Influential Values in the Annual Survey of Public Employment and Payroll.” In Proceedings of the 2012Search in Google Scholar

Research Conference of the Federal Committee on Statistical Methods. Office of Management and Budget. Washington, DC. Available at: https://fcsm.sites.usa.gov/files/2014/05/Barth_2012FCSM_III-D.pdf (accessed October 10, 2014) Beaumont, J.-F. 2004. Robust Estimation of a Finite Population Total in the Presence of Influential Units. Report for the Office for National Statistics, dated July 23, 2004. Office for National Statistics, Newport, U.K.Search in Google Scholar

Beaumont, J.-F., and A. Alavi. 2004. “Robust Generalized Regression Estimation.” Survey Methodology 30: 195-208.Search in Google Scholar

Black, J. 2001. “Changes in Sampling Units in Surveys of Businesses.” In Proceedings of the Federal Committee on Statistical Methods Research Conference. Office of Management and Budget. Washington, DC. Available at: http://www.fcsm.gov/files/2014/05/2001FCSM_Black.pdf (accessed October 20, 2014)Search in Google Scholar

Chambers, R.L. and R. Ren. 2004. “Outlier Robust Imputation of Survey Data.” In Proceedings of the American Statistical Association, Section on Survey Research Methods [CD-ROM]. American Statistical Association. Alexandria, VA. 3336-3344. Available at: http://www.amstat.org/sections/SRMS/Proceedings/y2004/files/Jsm2004-000559.pdf (accessed October 20, 2014) Chambers, R.L., P. Kokic, P. Smith, and M. Search in Google Scholar

Cruddas. 2000. “Winsorization for Identifying and Treating Outliers in Business Surveys.” In Proceedings of the Second International Conference on Establishment Surveys. Statistics Canada. Ottawa, Canada. 717-726.Search in Google Scholar

Clark, R. 1995. “Winsorization Methods in Sample Surveys.” Masters Thesis. Department of Statistics. Australia National University. Available at: http://hdl.handle.net/10440/1031 (accessed October 21, 2014) Search in Google Scholar

Farrell, P.J. and M. Salibian-Barrera. 2006. “A Comparison of Several Robust Estimators for a Finite Population Mean.” Journal of Statistical Studies 26: 29-43.Search in Google Scholar

Hampel, F.R., E.M. Ronchetti, P.J. Rousseeuw, and S.A. Werner. 1986. Robust Statistics. An Approach Based on Influence Functions. New York: John Wiley & Sons.Search in Google Scholar

Huang, E. 1984. “An Imputation Study for the Monthly Retail Trade Survey.” In Proceedings Joint Statistical Meeting, Survey Research Methods Section, American Statistical Association. Alexandria, VA. 610-615.Search in Google Scholar

Huber, P.J. 1964. “Robust Estimation of a location parameter.” Annals of Mathematical Statistics. Institute of Mathematical Statistics 35: 73-101.10.1214/aoms/1177703732Search in Google Scholar

Hidiroglou, M.A. and J.-M. Berthelot. 1986. “Statistical Editing and Imputation for Periodic Business Surveys.” Survey Methodology 12: 73-83.Search in Google Scholar

Hulliger, B. 1995. “Outlier Robust Horvitz-Thompson Estimators.” Survey Methodology 21: 79-81.Search in Google Scholar

Hunt, J.W., J.S. Johnson, and C.S. King. 1999. “Detecting Outliers in the Monthly Retail Trade Survey Using the Hidiroglou-Berthelot Method.” In Proceedings of the Section on Survey Research Methods. American Statistical Association. Alexandria, VA. 539-543. Available at: http://www.amstat.org/sections/SRMS/Proceedings/papers/1999_093.pdf (accessed October 20, 2014)Search in Google Scholar

Kokic, P.N. and P.A. Bell. 1994. “Optimal Winsorising Cut-Offs for a Stratified Finite Population Estimator.” Journal of Official Statistics 10: 419-435.Search in Google Scholar

Lewis, D. 2007. “Winsorisation for estimates of change.” Proceedings of the Third International Conference on Establishment Surveys. American Statistical Association. Alexandria, VA. 1165-1172.Search in Google Scholar

Mulry, M.H. and B. Oliver. 2009. “A Simulation Study of Treatments of Influential Values in the Monthly Retail Trade Survey.” JSM Proceedings, Survey Research Methods Section. American Statistical Association. Alexandria, VA. 2979-2993. Available at: http://www.amstat.org/sections/SRMS/Proceedings/y2009/Files/304284.pdf (accessed October 20, 2014)Search in Google Scholar

Mulry, M.H. and R. Feldpausch. 2007a. “Investigation of Treatment of Influential Values.” Proceedings of the Third International Conference on Establishment Surveys. American Statistical Association. Alexandria, VA. 1173-1179.Search in Google Scholar

Mulry, M.H. and R. Feldpausch. 2007b. “Treating Influential Values in a Monthly Retail Trade Survey.” Proceedings of the Survey Methods Section, SSC Annual Meeting. Statistical Society of Canada. Ottawa, Ontario, Canada. Available at: http://www.ssc.ca/survey/documents/SSC2007_M_Mulry.pdf (accessed October 20, 2014)Search in Google Scholar

Ren, R. and R.L. Chambers. 2003. “Outlier Robust Imputation of Survey Data via Reverse Calibration.” S3RI Methodology Working Paper M03/19. Southampton Statistical Sciences Research Institute, University of Southampton, U.K. Available at: http://www.eprints.soton.ac.uk/8169/1/8169-01.pdf (accessed October 20, 2014)Search in Google Scholar

Rousseeuw, P.J. 1984. “Least Median of Squares Regression.” Journal of the American Statistical Association 79: 871-880.10.1080/01621459.1984.10477105Search in Google Scholar

Rousseeuw, P.J. and A.M. Leroy. 1987. Robust Regression and Outlier Detection. New York: John Wiley & Sons.10.1002/0471725382Search in Google Scholar

Särndal, C.-E., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. New York: Springer-Verlag.10.1007/978-1-4612-4378-6Search in Google Scholar

Thompson, J.R. 2000. Simulation: A Modeler’s Approach. New York: John Wiley and Sons. 87-110.Search in Google Scholar

Thompson, K.J. and K.T. Washington. 2013. “Challenges in the Treatment of Unit Nonresponse for Selected Business Surveys: A Case Study.” Survey Methods: Insights from the Field. Available at: http://surveyinsights.org/?p¼2991 (accessed October 20, 2014)Search in Google Scholar

Thompson, K.J. and R.S. Sigman. 1999. “Statistical Methods for Developing Ratio Edit Tolerances for Economic Data.” Journal Official Statistics 15: 517-535. Search in Google Scholar

eISSN:
2001-7367
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Mathematics, Probability and Statistics