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Multiple Imputation of Missing Income Data in the National Health Interview Survey

Citations

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Cited by:

  1. Christian Aßmann & Ariane Würbach & Solange Goßmann & Ferdinand Geissler & Anika Bela, 2017. "Nonparametric Multiple Imputation for Questionnaires with Individual Skip Patterns and Constraints: The Case of Income Imputation in the National Educational Panel Study," Sociological Methods & Research, , vol. 46(4), pages 864-897, November.
  2. Morehart, Mitch & Milkove, Dan & Xu, Yang, 2014. "Multivariate Farm Debt Imputation in the Agricultural Resource Management Survey (ARMS)," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169401, Agricultural and Applied Economics Association.
  3. Anne Valentine & Ilhom Akobirshoev & Monika Mitra, 2019. "Intimate Partner Violence among Women with Disabilities in Uganda," IJERPH, MDPI, vol. 16(6), pages 1-13, March.
  4. B Rey deCastro, 2014. "Acrolein and Asthma Attack Prevalence in a Representative Sample of the United States Adult Population 2000 – 2009," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-10, May.
  5. Tatjana Miljkovic & Ying-Ju Chen, 2021. "A new computational approach for estimation of the Gini index based on grouped data," Computational Statistics, Springer, vol. 36(3), pages 2289-2311, September.
  6. Zhong, Hua & Hu, Wuyang, 2015. "Farmers’ Willingness to Engage in Best Management Practices: an Application of Multiple Imputation," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196962, Southern Agricultural Economics Association.
  7. Caterina Giusti, 2009. "Multiple Imputation of Missing Income Data in the Survey on Income and Living Conditions," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 63-80, January.
  8. Cameron Deal & Shea Greenberg & Gilbert Gonzales, 2024. "Sexual identity, poverty, and utilization of government services," Journal of Population Economics, Springer;European Society for Population Economics, vol. 37(2), pages 1-31, June.
  9. Kilic, Talip & Zezza, Alberto & Carletto, Calogero & Savastano, Sara, 2017. "Missing(ness) in Action: Selectivity Bias in GPS-Based Land Area Measurements," World Development, Elsevier, vol. 92(C), pages 143-157.
  10. Uma Radhakrishnan, 2010. "A Dynamic Structural Model of Contraceptive Use and Employment Sector Choice for Women in Indonesia," Working Papers 10-28, Center for Economic Studies, U.S. Census Bureau.
  11. English, Eric & von Haefen, Roger H. & Herriges, Joseph & Leggett, Christopher & Lupi, Frank & McConnell, Kenneth & Welsh, Michael & Domanski, Adam & Meade, Norman, 2018. "Estimating the value of lost recreation days from the Deepwater Horizon oil spill," Journal of Environmental Economics and Management, Elsevier, vol. 91(C), pages 26-45.
  12. Yongwei Chen & Dahai Fu, 2015. "Measuring income inequality using survey data: the case of China," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(2), pages 299-307, June.
  13. Zhang, Lixuan & Yencha, Christopher, 2022. "Examining perceptions towards hiring algorithms," Technology in Society, Elsevier, vol. 68(C).
  14. Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association.
  15. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
  16. He Yulei & Shimizu Iris & Schappert Susan & Xu Jianmin & Beresovsky Vladislav & Khan Diba & Valverde Roberto & Schenker Nathaniel, 2016. "A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014," Journal of Official Statistics, Sciendo, vol. 32(1), pages 147-164, March.
  17. repec:iab:iabfme:201202(en is not listed on IDEAS
  18. Fujishiro, Kaori & Xu, Jun & Gong, Fang, 2010. "What does "occupation" represent as an indicator of socioeconomic status?: Exploring occupational prestige and health," Social Science & Medicine, Elsevier, vol. 71(12), pages 2100-2107, December.
  19. John L. Czajka & Gabrielle Denmead, "undated". "Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys," Mathematica Policy Research Reports 19724257b78544bdbd55f15be, Mathematica Policy Research.
  20. Drechsler, Jörg & Kiesl, Hans, 2014. "Beat the heap - an imputation strategy for valid inferences from rounded income data," IAB-Discussion Paper 201402, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  21. Hai Zhong, 2010. "The impact of missing data in the estimation of concentration index: a potential source of bias," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(3), pages 255-266, June.
  22. Herrmann, Mariesa A. & Rockoff, Jonah E., 2013. "Do menstrual problems explain gender gaps in absenteeism and earnings?," Labour Economics, Elsevier, vol. 24(C), pages 12-22.
  23. Luca Salvati & Marco Zitti & Luigi Perini, 2009. "Spazio rurale e Land use quality: una proposta per un sistema di indicatori a scala comunale in Italia," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 101-131, January.
  24. Roberto Gismondi, 2009. "Optimal Provisional Estimation in Short-term Surveys," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 5-34, January.
  25. Manuel Gomes & Nils Gutacker & Chris Bojke & Andrew Street, 2016. "Addressing Missing Data in Patient‐Reported Outcome Measures (PROMS): Implications for the Use of PROMS for Comparing Provider Performance," Health Economics, John Wiley & Sons, Ltd., vol. 25(5), pages 515-528, May.
  26. Juana Sanchez & Sydney Noelle Kahmann, 2017. "R&D, Attrition and Multiple Imputation in BRDIS," Working Papers 17-13, Center for Economic Studies, U.S. Census Bureau.
  27. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.
  28. Manuel Gomes & Nils Gutacker & Chris Bojke & Andrew Street, 2014. "Addressing missing data in patient-reported outcome measures (PROMs): implications for comparing provider performance," Working Papers 101cherp, Centre for Health Economics, University of York.
  29. Luigi Costanzo & Filippo Oropallo & Stefania Rossetti, 2009. "Le dinamiche produttive d’impresa nei sistemi locali del lavoro," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 81-100, January.
  30. Eisele, Martin & Zhu, Junyi, 2013. "Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions," EconStor Preprints 100007, ZBW - Leibniz Information Centre for Economics.
  31. Federica Battellini & Alessandra Coli & Francesca Tartamella, 2009. "La SAM come strumento di integrazione e analisi," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 11(2-3), pages 35-62, January.
  32. Jaenichen, Ursula & Sakshaug, Joseph, 2012. "Multiple imputation of household income in the first wave of PASS," FDZ Methodenreport 201202_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  33. Currie, Janet & Decker, Sandra & Lin, Wanchuan, 2008. "Has public health insurance for older children reduced disparities in access to care and health outcomes?," Journal of Health Economics, Elsevier, vol. 27(6), pages 1567-1581, December.
  34. Speidel, Matthias & Drechsler, Jörg & Jolani, Shahab, 2018. "R package hmi: a convenient tool for hierarchical multiple imputation and beyond," IAB-Discussion Paper 201816, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  35. Sonya Vartivarian & John L. Czajka & Michael Weber, "undated". "Measuring Disclosure Risk and an Examination of the Possibilities of Using Synthetic Data in the Individual Income Tax Return Public Use File," Mathematica Policy Research Reports ab85aed60a3e429786cfcbfdc, Mathematica Policy Research.
  36. Corinne Reczek & Hui Liu & Dustin Brown, 2014. "Cigarette Smoking in Same-Sex and Different-Sex Unions: The Role of Socioeconomic and Psychological Factors," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(4), pages 527-551, August.
  37. repec:mpr:mprres:5634 is not listed on IDEAS
  38. Zhong, Hua & Hu, Wuyang & Penn, Jerrod M., 2018. "Application of Multiple Imputation in Dealing with Missing Data in Agricultural Surveys: The Case of BMP Adoption," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.
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