Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Xiao Song & Ching‐Yun Wang, 2019. "GMM nonparametric correction methods for logistic regression with error‐contaminated covariates and partially observed instrumental variables," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 46(3), pages 898-919, September.
- van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
- Carroll, Raymond J. & Freedman, Laurence & Pee, David, 1997. "Design aspects of calibration studies in nutrition, with analysis of missing data in linear measurement error models," SFB 373 Discussion Papers 1997,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Nicoletti, Cheti & Peracchi, Franco & Foliano, Francesca, 2011.
"Estimating Income Poverty in the Presence of Missing Data and Measurement Error,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 61-72.
- Cheti Nicoletti & Franco Peracchi & Francesca Foliano, 2011. "Estimating Income Poverty in the Presence of Missing Data and Measurement Error," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 61-72, January.
- Cheti Nicoletti & Franco Peracchi & Francesca Foliano, 2009. "Estimating Income Poverty in the Presence of Missing Data and Measurement Error," CEIS Research Paper 145, Tor Vergata University, CEIS, revised 30 Sep 2009.
- Cheti Nicoletti & Franco Peracchi & Francesca Foliano, 2009. "Estimating Income Poverty in the Presence of Missing Data and Measurement Error," SOEPpapers on Multidisciplinary Panel Data Research 252, DIW Berlin, The German Socio-Economic Panel (SOEP).
- Wang, Qihua & Sun, Zhihua, 2007. "Estimation in partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1470-1493, August.
- Eugster, Manuel J.A. & Leisch, Friedrich, 2011. "Weighted and robust archetypal analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1215-1225, March.
- Min Wang & Xiaoqian Sun & Tao Lu, 2015. "Bayesian structured variable selection in linear regression models," Computational Statistics, Springer, vol. 30(1), pages 205-229, March.
- Casella, George & Moreno, Elias, 2006. "Objective Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 157-167, March.
- Buzas, J. S. & Stefanski, L. A., 1996. "A note on corrected-score estimation," Statistics & Probability Letters, Elsevier, vol. 28(1), pages 1-8, June.
- Paul T. von Hippel, 2013. "The Bias and Efficiency of Incomplete-Data Estimators in Small Univariate Normal Samples," Sociological Methods & Research, , vol. 42(4), pages 531-558, November.
- C. Y. Wang & Yijian Huang & Edward C. Chao & Marjorie K. Jeffcoat, 2008. "Expected Estimating Equations for Missing Data, Measurement Error, and Misclassification, with Application to Longitudinal Nonignorable Missing Data," Biometrics, The International Biometric Society, vol. 64(1), pages 85-95, March.
- Hua Liang & Suojin Wang & Raymond J. Carroll, 2007. "Partially linear models with missing response variables and error-prone covariates," Biometrika, Biometrika Trust, vol. 94(1), pages 185-198.
- Grace Y. Yi & Yanyuan Ma & Raymond J. Carroll, 2012. "A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error," Biometrika, Biometrika Trust, vol. 99(1), pages 151-165.
More about this item
KeywordsError-in-variables; Missing data; Simulation extrapolation; Corrected score;
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:compst:v:35:y:2020:i:3:d:10.1007_s00180-020-00976-2. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.