1. bookVolume 37 (2021): Issue 4 (December 2021)
Journal Details
License
Format
Journal
eISSN
2001-7367
First Published
01 Oct 2013
Publication timeframe
4 times per year
Languages
English
access type Open Access

Estimation of Domain Means from Business Surveys in the Presence of Stratum Jumpers and Nonresponse

Published Online: 26 Dec 2021
Page range: 1059 - 1078
Received: 01 Mar 2019
Accepted: 01 May 2021
Journal Details
License
Format
Journal
eISSN
2001-7367
First Published
01 Oct 2013
Publication timeframe
4 times per year
Languages
English
Abstract

Misclassified frame records (also called stratum jumpers) and low response rates are characteristic for business surveys. In the context of estimation of the domain parameters, jumpers may contribute to extreme variation in sample weights and skewed sampling distributions of the estimators, especially for domains with a small number of observations. There is limited literature about the extent to which these problems may affect the performance of the ratio estimators with nonresponse-adjusted weights. To address this gap, we designed a simulation study to explore the properties of the Horvitz-Thompson type ratio estimators, with and without smoothing of the weights, under different scenarios. The ratio estimator with propensity-adjusted weights showed satisfactory performance in all scenarios with a high response rate. For scenarios with a low response rate, the performance of this estimator improved with an increase in the proportion of jumpers in the domain. The smoothed estimators that we studied performed well in scenarios with non-informative weights, but can become markedly biased when the weights are informative, irrespective of response rate. We also studied the performance of the ’doubled half’ bootstrap method for variance estimation. We illustrated an application of the methods in a real business survey.

Keywords

Antal, E. and Y. Tillé. 2014. “A New Resampling Method for Sampling Designs Without Replacement: the Doubled Half Bootstrap.” Computational Statistics 29: 1345–1363. DOI: https://doi.org/10.1007/s00180-014-0495-0.10.1007/s00180-014-0495-0 Search in Google Scholar

Beaumont, J.-F. 2008. “A New Approach to Weighting and Inference in Sample Surveys.” Biometrika 95: 539–553. DOI: http:s//doi.org/10.1093/biomet/asn028.10.1093/biomet/asn028 Search in Google Scholar

Beaumont, J.-F., A. Beliveau, and D. Haziza. 2015. “Clarifying Some Aspects of Variance Estimation in Two-Phase Sampling.” Journal of Survey Statistics and Methodology 3: 524–542. DOI: https://doi.org/10.1093/jssam/smv022.10.1093/jssam/smv022 Search in Google Scholar

Beaumont, J.-F., and Z. Patak. 2012. “On the Generalized Bootstrap for Sample Surveys with Special Attention to Poisson Sampling.” International Statistical Review 80: 127–148. DOI: https://dx.doi.org/10.1111/j.1751-5823.2011.00166.x.10.1111/j.1751-5823.2011.00166.x Search in Google Scholar

Beaumont, J.-F., and L.-P. Rivest. 2009. “Dealing with Outliers in Survey Data.” In Handbook of Statistics, vol. 29A, Sample Surveys: Design, Methods and Applications, edited by D. Pfeffermann and C.R. Rao, 247–279. Amsterdam: Elsevier. DOI: https://doi.org/10.1016/S0169-7161(08)00011-4.10.1016/S0169-7161(08)00011-4 Search in Google Scholar

Chen, Q., M.R. Elliott, D. Haziza, Y. Yang, M. Ghosh, R.J.A. Little, J. Sedransk, M. Thompson. 2017. “Approaches to improving survey-weighted estimates”. Statistical Science 32(2): 227–248. DOI: https://doi.org/10.1214/17-STS609.10.1214/17-STS609 Search in Google Scholar

Cook, S., P. LeBaron, L. Flicker, and T.S. Flanigan. 2009. “Applying Incentives to Establishment Surveys: A Review of the Literature.” In Proceedings of the Section on Survey Research Methods: American Statistical Association, May 14–17, 2009. 5639–5647. Available at: http://www.asasrms.org/Proceedings/y2009/Files/400022.pdf (accessed March 2019). Search in Google Scholar

Favre-Martinoz, C., D. Haziza, and J.-F. Beaumont. 2015. “A Method of Determining the Winsorization Threshold, With an Application to Domain Estimation.” Survey Methodology 41: 57–77. Search in Google Scholar

Haziza, D., and E. Lesage. 2016. “A Discussion of Weighting Procedures for Unit Nonresponse.” Journal of Official Statistics 32: 129–145. DOI: https://doi.org/10.1515/JOS-2016-0006.10.1515/jos-2016-0006 Search in Google Scholar

Institute for Work and Health. 2011. “Benchmarking Organizational Leading Indicators for the Prevention and Management of Injuries and Illnesses: Final Report.” Available at: https://www.iwh.on.ca/sites/iwh/files/iwh/reports/iwh_report_benchmarking_organizational_leading_indicators_2011.pdf (accessed March 2019). Search in Google Scholar

Institute for Work and Health. 2013. “Measures in the Ontario Leading Indicators Project (OLIP) Survey.” Available at: https://www.iwh.on.ca/sites/iwh/files/iwh/reports/iwh_project_olip_about_the_measures_august_2013.pdf (accessed March 2019). Search in Google Scholar

Kim., J.K., and J.J. Kim. 2007. “Nonresponse Weighting Adjustment Using Estimated Response Probability.” The Canadian Journal of Statistics 35: 501–514. DOI: https://doi.org/10.1002/cjs.5550350403.10.1002/cjs.5550350403 Search in Google Scholar

Kim, J.K., A. Navarro, and W.A. Fuller. 2006. “Replication Variance Estimation for Two-Phase Stratified Sampling.” Journal of the American Statistical Association 101: 312–320.10.1198/016214505000000763 Search in Google Scholar

Kim, J.K., and C.L. Yu. 2011. “Replication Variance Estimation Under Two-phase Sampling.” Survey Methodology 37: 67–74. Search in Google Scholar

Korn, E.L., and B.I. Graubard. 1999. Analysis of Health Surveys. New York: Wiley. DOI: https://doi.org/10.1002/9781118032619.fmatter.10.1002/9781118032619.fmatter Search in Google Scholar

Lachin, J.M. 2011. Biostatistical Methods: The Assessment of Relative Risks. 2nd edition, Hoboken, NJ: Wiley. DOI: https://doi.org/10.1002/sim.1167.10.1002/sim.1167 Search in Google Scholar

Landsman, V., and B.I. Graubard. 2013. “Efficient Analysis of Case-control Studies With Sample Weights.” Statistics in Medicine 32: 347–360. DOI: https://doi.org/10.1002/sim.5530.10.1002/sim.5530 Search in Google Scholar

Lee, H. 1995. “Outliers in Business Surveys.” In Business Survey Methods, edited by B.G. Cox, D.A. Binder, B.N. Chinnappa, A. Christianson, M.J. Colledge and P.S. Kott, 503–526. New York: Wiley. DOI: https://doi.org/10.1002/9781118150504.ch26.10.1002/9781118150504.ch26 Search in Google Scholar

Li, Y., B.I. Graubard, and R. DiGaetano. 2011. “Weighting Methods for Population-based Case-control Studies With Complex Sampling.” JRSS(C) 60: 165–185. DOI: https://doi.org/10.1111/j.1467-9876.2010.00731.x.10.1111/j.1467-9876.2010.00731.x Search in Google Scholar

Lohr, S.L., M.K. Riddles, and D. Morganstein. 2016. “Tests for Evaluating Nonresponse Bias in Surveys.” Survey Methodology 42: 195–218. Search in Google Scholar

Little, R.J., and S. Vartivarian. 2003. “On Weighting the Rates in Non-response Weights.” Statistics in Medicine 22: 1589–1599. DOI: https://doi.org/10.1002/sim.1513.10.1002/sim.1513 Search in Google Scholar

MacNeil, D., and S. Pursey. 2002. “Dealing With Industry Misclassifications in the Unified Enterprise Survey.” In Proceedings of the Survey Methods Section: SSC Annual Meeting, May 2002: 51–56. Search in Google Scholar

Mashreghi, Z., D. Haziza, and C. Léger. 2016. “A Survey of Bootstrap Methods in Finite Population Sampling.” Statistics Surveys 10: 1–52. DOI: https://doi.org/10.1214/16-SS113.10.1214/16-SS113 Search in Google Scholar

Nordlöf, H., K. Wijk, and K.-E. Westergren. 2015. “Perceptions of Work Environment Priorities: Are there any Differences by Company Size? – An Ecological Study.” Work 52: 697–706. DOI: https://doi.org/10.3233/WOR-152123.10.3233/WOR-152123 Search in Google Scholar

Pfeffermann, D., and M. Sverchkov. 1999. “Parametric and Semi-parametric Estimation of Regression Models Fitted to Survey Data.” Sankhya B 61: 166–186. Search in Google Scholar

Rao, J.N.K. 1966. “Alternative Estimators in PPS Sampling for Multiple Characteristics.” Sankhya: The Indian Journal of Statistics 28: 47–60. Search in Google Scholar

Rao, J.N.K. and C.F.J. Wu. 1988. “Resampling Inference With Complex Survey Data.” Journal of the American Statistical Association 83: 231–241. DOI: https://doi.org/10.1080/01621459.1988.10478591.10.1080/01621459.1988.10478591 Search in Google Scholar

Rao, J.N.K., C.F.J. Wu, and K. Yue. 1992. “Some Recent Work on Resampling Methods for Complex Surveys.” Survey Methodology 18: 209–217. Search in Google Scholar

Valliant, R., J.A. Dever, and F. Kreuter. 2013. “Basic Steps in Weighting.” In Practical Tools for Designing and Weighting Survey Samples, edited by R. Valliant, J.A. Dever, and F. Kreuter, 307–348. New York: Springer. DOI: https://doi.org/10.1007/978-3-319-93632-1_13.10.1007/978-3-319-93632-1_13 Search in Google Scholar

U.S. Department of Labor; Bureau of Labor Statistics; Office of Survey Methods Research. Household and establishment survey response rates. Chart 2. Establishment surveys: overall unit response rates. Washington DC. Available at: https://www.bls.gov/osmr/response-rates/home.htm (accessed October 2019). Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo