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Non‐response adjustment of survey estimates based on auxiliary variables subject to error

dc.contributor.authorWest, Brady T.en_US
dc.contributor.authorLittle, Roderick J. A.en_US
dc.date.accessioned2013-03-05T18:17:13Z
dc.date.available2014-05-01T14:28:08Zen_US
dc.date.issued2013-03en_US
dc.identifier.citationWest, Brady T.; Little, Roderick J. A. (2013). "Non‐response adjustment of survey estimates based on auxiliary variables subject to error." Journal of the Royal Statistical Society: Series C (Applied Statistics) 62(2). <http://hdl.handle.net/2027.42/96670>en_US
dc.identifier.issn0035-9254en_US
dc.identifier.issn1467-9876en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/96670
dc.publisherBlackwell Publishing Ltden_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherNon‐Response Adjustment of Survey Estimatesen_US
dc.subject.otherAuxiliary Variablesen_US
dc.subject.otherPattern–Mixture Modelsen_US
dc.subject.otherPanel Arbeitsmarkt Und Soziale Sicherung (Labour Market and Social Security) Surveyen_US
dc.subject.otherMeasurement Erroren_US
dc.subject.otherNon‐Ignorable Missing Dataen_US
dc.titleNon‐response adjustment of survey estimates based on auxiliary variables subject to erroren_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/96670/1/j.1467-9876.2012.01058.x.pdf
dc.identifier.doi10.1111/j.1467-9876.2012.01058.xen_US
dc.identifier.sourceJournal of the Royal Statistical Society: Series C (Applied Statistics)en_US
dc.identifier.citedreferenceRaghunathan, T. E., Lepkowski, J. M., Van Hoewyk, J. and Solenberger, P. ( 2001 ) A multivariate technique for multiply imputing missing values using a sequence of regression models. Surv. Methodol., 27, 85 – 95.en_US
dc.identifier.citedreferenceGroves, R. M. ( 2006 ) Nonresponse rates and nonresponse bias in household surveys. Publ. Opin. Q., 70, 646 – 675.en_US
dc.identifier.citedreferenceGroves, R. M., Wagner, J. and Peytcheva, E. ( 2007 ) Use of interviewer judgments about attributes of selected respondents in post‐survey adjustments for unit nonresponse: an illustration with the National Survey of Family Growth. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass.en_US
dc.identifier.citedreferenceHeeringa, S. G., West, B. T. and Berglund, P. A. ( 2010 ) Applied Survey Data Analysis. Boca Raton: Chapman and Hall–CRC Press.en_US
dc.identifier.citedreferenceKreuter, F., Olson, K., Wagner, J., Yan, T., Ezzati‐Rice, T. M., Casas‐Cordero, C., Lemay, M., Peytchev, A., Groves, R. M. and Raghunathan, T. E. ( 2010 ) Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys. J. R. Statist. Soc. A, 173, 389 – 407.en_US
dc.identifier.citedreferenceLessler, J. and Kalsbeek, W. ( 1992 ) Nonresponse: dealing with the problem. In Nonsampling Errors in Surveys, ch. 8. New York: Wiley‐Interscience.en_US
dc.identifier.citedreferenceLittle, R. J. A. ( 1994 ) A class of pattern‐mixture models for normal incomplete data. Biometrika, 81, 471 – 483.en_US
dc.identifier.citedreferenceLittle, R. J. A. and Rubin, D. B. ( 2002 ) Statistical Analysis with Missing Data, 2nd edn. Hoboken: Wiley‐Interscience.en_US
dc.identifier.citedreferenceLittle, R. J. A. and Vartivarian, S. ( 2003 ) On weighting the rates in nonresponse weights. Statist. Med., 22, 1589 – 1599.en_US
dc.identifier.citedreferenceLittle, R. J. A. and Vartivarian, S. ( 2005 ) Does weighting for nonresponse increase the variance of survey means? Surv. Methodol., 31, 161 – 168.en_US
dc.identifier.citedreferenceLittle, R. J. A. and Wang, Y. ( 1996 ) Pattern‐mixture models for multivariate incomplete data with covariates. Biometrics, 52, 98 – 111.en_US
dc.identifier.citedreferenceLumley, T. ( 2010 ) Complex Surveys: a Guide to Analysis using R. Hoboken: Wiley.en_US
dc.identifier.citedreferenceMcCulloch, S. K., Kreuter, F. and Calvano, S. ( 2010 ) Interviewer observed vs. reported respondent gender: implications on measurement error. A. Meet. American Association for Public Opinion Research, Chicago, May 14th.en_US
dc.identifier.citedreferencePickering, K., Thomas, R. and Lynn, P. ( 2003 ) Testing the shadow sample approach for the English House Condition survey. Report. National Centre for Social Research, London.en_US
dc.identifier.citedreferenceR Development Core Team ( 2011 ) R: a Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.en_US
dc.identifier.citedreferenceRubin, D. B. ( 1976 ) Inference and missing data. Biometrika, 63, 581 – 592.en_US
dc.identifier.citedreferenceRubin, D. B. ( 1987 ) Multiple Imputation for Non‐response in Surveys. New York: Wiley.en_US
dc.identifier.citedreferenceShardell, M., Hicks, G. E., Miller, R. R., Langenberg, P. and Magaziner, J. ( 2010 ) Pattern‐mixture models for analyzing normal outcome data with proxy respondents. Statist. Med., 29, 1522 – 1538.en_US
dc.identifier.citedreferenceStataCorp ( 2011 ) Stata Statistical Software: Release 12. College Station: StataCorp.en_US
dc.identifier.citedreferenceTipping, S. and Sinibaldi, J. ( 2010 ) Examining the trade off between sampling and targeted non‐response error in a targeted non‐response follow‐up. Int. Total Survey Error Wrkshp, Stowe, June 15th.en_US
dc.identifier.citedreferenceTrappmann, M., Gundert, S., Wenzig, C. and Gebhardt, D. ( 2010 ) PASS: a household panel survey for research on unemployment and poverty. Schmoll. Jahrb. Zeits. Wirtschafts. Sozialwissen., 130, 609 – 622.en_US
dc.identifier.citedreferenceWest, B. T. ( 2013 ) An examination of the quality and utility of interviewer observations in the National Survey of Family Growth. J. R. Statist. Soc. A, 176, in the press.en_US
dc.identifier.citedreferenceAndridge, R. R. and Little, R. J. A. ( 2009 ) Extensions of proxy pattern‐mixture analysis for survey non‐response. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass., 2468 – 2482.en_US
dc.identifier.citedreferenceAndridge, R. R. and Little, R. J. A. ( 2011 ) Proxy pattern‐mixture analysis for survey nonresponse. J. Off. Statist., 27, 153 – 180.en_US
dc.identifier.citedreferenceBaskin, R. M., Zuvekas, S. H. and Ezzati‐Rice, T. M. ( 2011 ) Proxy pattern‐mixture analysis of missing health expenditure variables in the Medical Expenditure Panel Survey. Int. Total Survey Error Wrkshp, Quebec, June 21st.en_US
dc.identifier.citedreferenceBeaumont, J.‐F. ( 2005 ) On the use of data collection process information for the treatment of unit non‐response through weight adjustment. Surv. Methodol., 31, 227 – 231.en_US
dc.identifier.citedreferenceBethlehem, J. ( 2002 ) Weighting nonresponse adjustments based on auxiliary information. In Survey Nonresponse (eds R. Groves, D. Dillman, J. Eltinge and R. Little ), pp. 275 – 287. New York: Wiley.en_US
dc.identifier.citedreferenceCampanelli, P., Sturgis, P. and Purdon, S. ( 1997 ) Can You Hear Me Knocking: an Investigation into the Impact of Interviewers on Survey Response Rates. London: Social and Community Planning Research.en_US
dc.identifier.citedreferenceDiSogra, C., Dennis, J. M. and Fahimi, M. ( 2010 ) On the quality of ancillary data available for address‐based sampling. Prac. Surv. Res. Meth. Sect. Am. Statist. Ass., 4174 – 4183.en_US
dc.identifier.citedreferenceFuller, W. ( 1987 ) A single explanatory variable. In Measurement Error Models, ch. 1. New York: Wiley.en_US
dc.identifier.citedreferenceGelman, A., Carlin, J. B., Stern, H. S. and Rubin, D. B. ( 2004 ) Bayesian Data Analysis, 2nd edn. Boca Raton: Chapman and Hall–CRC Press.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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