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Citations for "Missing-Data Adjustments in Large Surveys"

by Little, Roderick J A

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  1. Eric French and John Jones, 2001. "The Effects of Health Insurance and Self-Insurance on Retirement Behavior," Computing in Economics and Finance 2001 24, Society for Computational Economics.
  2. Steven Haider & Melvin Stephens Jr., 2004. "Is There a Retirement-Consumption Puzzle? Evidence Using Subjective Retirement Expectations," NBER Working Papers 10257, National Bureau of Economic Research, Inc.
  3. Grabka, Markus & Westermeier, Christian, 2014. "Estimating the Impact of Alternative Multiple Imputation Methods on Longitudinal Wealth Data," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100353, Verein für Socialpolitik / German Economic Association.
  4. Daniel Schunk, 2007. "A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey," MEA discussion paper series 07121, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  5. Joachim R. Frick & Markus M. Grabka, 2007. "Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," SOEPpapers on Multidisciplinary Panel Data Research 49, DIW Berlin, The German Socio-Economic Panel (SOEP).
  6. Hendrik Jürges & Lars Thiel & Tabea Bucher-Koenen & Johannes Rausch & Morten Schuth & Axel Börsch-Supan, 2014. "Health, Financial Incentives, and Early Retirement: Microsimulation Evidence for Germany," NBER Chapters, in: Social Security Programs and Retirement Around the World: Disability Insurance Programs and Retirement, pages 285-330 National Bureau of Economic Research, Inc.
  7. Schunk, Daniel, 2007. "The German SAVE survey: documentation and methodology," Sonderforschungsbereich 504 Publications 07-08, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  8. Verbeek, M. & Nijman, T., 1992. "Incomplete Panels and Selection Bias: A Survey," Papers 9207, Tilburg - Center for Economic Research.
  9. Joost Ginkel & Pieter Kroonenberg, 2014. "Using Generalized Procrustes Analysis for Multiple Imputation in Principal Component Analysis," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 242-269, July.
  10. Rasner, Anika & Frick, Joachim R. & Grabka, Markus M., 2013. "Statistical Matching of Administrative and Survey Data: An Application to Wealth Inequality Analysis," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 192-224.
  11. Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
  12. Miguel Székely & Nora Lustig & Martin Cumpa & José Antonio Mejía-Guerra, 2000. "Do We Know How Much Poverty There Is?," Research Department Publications 4239, Inter-American Development Bank, Research Department.
  13. S. Nazli Wasti, 2001. "Predictors of Trust in Buyer-Supplier Relations: A Contextual and Cultural Comparison of Japan and Turkey," CIRJE F-Series CIRJE-F-108, CIRJE, Faculty of Economics, University of Tokyo.
  14. Gabriele Beissel-Durrant & Chris Skinner, 2003. "Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error," CeMMAP working papers CWP12/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Siddique, Juned & Belin, Thomas R., 2008. "Using an Approximate Bayesian Bootstrap to multiply impute nonignorable missing data," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 405-415, December.
  16. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
  17. Michael Hurd & Elaine Reardon, 2003. "Real Wealth Changes from 1982 to 1991 Among the Newly Retired," Working Papers 03-15, RAND Corporation.
  18. Siddique, Juned & Harel, Ofer, 2009. "MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i09).
  19. Lamu, Admassu N. & Olsen, Jan Abel, 2016. "The relative importance of health, income and social relations for subjective well-being: An integrative analysis," Social Science & Medicine, Elsevier, vol. 152(C), pages 176-185.
  20. Giuseppe Arbia & Giuseppe Espa & Diego Giuliani, 2015. "Dirty spatial econometrics," DEM Discussion Papers 2015/09, Department of Economics and Management.
  21. Chuang, Emmeline & Wells, Rebecca, 2010. "The role of inter-agency collaboration in facilitating receipt of behavioral health services for youth involved with child welfare and juvenile justice," Children and Youth Services Review, Elsevier, vol. 32(12), pages 1814-1822, December.
  22. Dang, Hai-Anh H. & Lanjouw, Peter F. & Serajuddin, Umar, 2014. "Updating poverty estimates at frequent intervals in the absence of consumption data : methods and illustration with reference to a middle-income country," Policy Research Working Paper Series 7043, The World Bank.
  23. Giuseppe Arbia & Giuseppe Espa & Diego Giuliani, 2016. "Dirty spatial econometrics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 177-189, January.
  24. Bollinger, Christopher R. & Hirsch, Barry, 2010. "Is Earnings Nonresponse Ignorable?," IZA Discussion Papers 5347, Institute for the Study of Labor (IZA).
  25. Ralf Münnich & Siegfried Gabler & Christian Bruch & Jan Pablo Burgard & Tobias Enderle & Jan-Philipp Kolb & Thomas Zimmermann, 2015. "Tabellenauswertungen im Zensus unter Berücksichtigung fehlender Werte," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 9(3), pages 269-304, December.
  26. Rässler, Susanne & Koller, Florian & Mäenpää, Christine, 2002. "A split questionnaire survey design applied to German media and consumer surveys," Discussion Papers 42b/2002, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
  27. repec:mpr:mprres:6788 is not listed on IDEAS
  28. Gianni La Cava & John Simon, 2003. "A Tale of Two Surveys: Household Debt and Financial Constraints in Australia," RBA Research Discussion Papers rdp2003-08, Reserve Bank of Australia.
  29. Seppo Laaksonen, 2003. "Alternative imputation techniques for complex metric variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(9), pages 1009-1020.
  30. Rässler, Susanne & Schnell, Rainer, 2004. "Multiple imputation for unit-nonresponse versus weighting including a comparison with a nonresponse follow-up study," Discussion Papers 65/2004, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
  31. Miguel Székely & Nora Lustig & Martin Cumpa & José Antonio Mejía-Guerra, 2000. "¿Sabemos qué tanta pobreza hay?," Research Department Publications 4240, Inter-American Development Bank, Research Department.
  32. Michael D. Hurd, 1998. "Anchoring Effects in the HRS: Experimental and Nonexperimental Evidence," NBER Technical Working Papers 0219, National Bureau of Economic Research, Inc.
  33. Luci Ellis & Jeremy Lawson & Laura Roberts-Thomson, 2003. "Housing Leverage in Australia," RBA Research Discussion Papers rdp2003-09, Reserve Bank of Australia.
  34. Natalie Shlomo & Chris J. Skinner & Barry Schouten, 2012. "Estimation of an indicator of the representativeness of survey response," LSE Research Online Documents on Economics 39124, London School of Economics and Political Science, LSE Library.
  35. Joachim Inkmann, 2001. "Accounting for Nonresponse Heterogeneity in Panel Data," CoFE Discussion Paper 01-03, Center of Finance and Econometrics, University of Konstanz.
  36. Frank Potter & Eric Grau & John Czajka & Dan Scheer & Mark Levitan, 2010. "Imputation Variance Estimation Protocols for the NAS Poverty Measure The New York City Poverty Measure Experience," Mathematica Policy Research Reports 77be49e0f91f41e888de5139e, Mathematica Policy Research.
  37. F. Di Lascio & Simone Giannerini & Alessandra Reale, 2015. "Exploring copulas for the imputation of complex dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 159-175, March.
  38. Olinsky, Alan & Chen, Shaw & Harlow, Lisa, 2003. "The comparative efficacy of imputation methods for missing data in structural equation modeling," European Journal of Operational Research, Elsevier, vol. 151(1), pages 53-79, November.
  39. Martin, Eisele & Zhu, Junyi, 2013. "Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions," MPRA Paper 57666, University Library of Munich, Germany.
  40. Gabriele Beissel Durrant, 2009. "Imputation Methods for Handling Item-Nonresponse in the Social Sciences: A Methodological Review," Working Papers id:2007, eSocialSciences.
  41. Christopher R. Bollinger & Barry T. Hirsch, 2010. "GDP & Beyond – die europäische Perspektive," Working Paper Series of the German Council for Social and Economic Data 165, German Council for Social and Economic Data (RatSWD).
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.