Multiple imputation based on conditional quantile estimation

Epidemiology Biostatistics and Public Health

Volumn 10, Issue 1, 2013, Pages

  Bottai, Matteo ^a   Zhen, Huiling ^b  

^a KAROLINSKA INSTITUTE   (Sweden)

^b UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

Conditional quantiles; Missing data; Multiple imputation; Quantile regression; Smoothing splines

Indexed keywords

EID: 84880484096     PISSN: None     EISSN: 22820930     Source Type: Journal    
DOI: 10.2427/875     Document Type: Article

References (42)

1. Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: J. Wiley & Sons.
2. Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. New York: Chapman & Hall.
3. Little, R. J. and Rubin, D. B. (2002). Statistical Analysis With Missing Data. New York: J. Wiley & Sons.
4. Allison, P. D. (2001). Missing Data. Sage University Papers Series on Quantitative Applications in the Social Sciences, 107-136.Thousand Oaks, CA:Sage.
5. McKnight, P. E., McKnight, K. M., Sidani, S., and Figueredo, A. J. (2007). Missing Data: A Gentle Introduction. New York, NY: Guilford.
6. Shafer, J. L. (1999). Multiple imputation: a primer. Statistical Methods in Medical Research 8, 3-15.
7. Schafer, J. L. and Graham, J. W. (2002). Multiple imputation: our view of the state of the art. Psychological Methods 7, 147-177.
8. Horton, N. J. and Kleinman, K. P. (2007). Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician 61, 79-90.
9. Harel, O. and Zhao, X.-H. (2007). Multiple imputation: Review of theory, implementation and software. Statistics in Medicine 26, 3057-3077.
10. Kenward, M. G. and Carpenter, J. (2007). Multiple imputation: current perspectives. Statistical Methods in Medical Research 16, 199-218.
11. Ruan, P. K. and Gray, R. J. (2008). Analyses of cumulative incidence functions via non-parametric multiple imputation. Statistics in Medicine 27, 5709-5724.
12. Moodie, E. E. M., Delaney, J. A. C., Lefebvre, G., and Platt, R. W. (2009). Missing confounding data in marginal structural models: A comparison of inverse probability weighting and multiple imputation. International Journal of Biostatistics 4.1.
13. Paddock, S. M. (2002). Bayesian non-parametric multiple imputation of partially observed data with ignorable nonresponse. Biometrika 89, 529-38.
14. Zhang, L.-C. (2004). Nonparametric markov chain bootstrap for multiple imputation. Computational Statistics & Data Analysis 45, 343-353.
15. Nielsen, S. F. (2001). Nonparametric conditional mean imputation. Journal of Statistical Planning and Inference. 99, 129-150.
16. Aerts, M., Claeskens, G., Hens, N., and Molenberghs, G. (2002). Local multiple imputation. Biometrika 89, 375-388.
17. Di Zio, M., Guarnera, U., and Luzi, O. (2007). Imputation through finite gaussian mixture models. Computational Statistics &i Data Analysis 51, 5305-5316.
18. Hunt, L. and Jorgensen (2003). Mixture model clustering for mixed data with missing information. Computational Statistics &; Data Analysis 41, 429-440.
19. Wang, D. and Chen, S. X. (2009). Empirical likelihood for estimating equations with missing values. Annals of Statistics 37, 490-517.
20. van Buuren, S. (2007). Multiple imputation of discrete and continuous data by fully conditional specification. Statistical Methods in Medical Research 16, 219-242.
21. Rubin, D. B. (1976). Inference and missing data. Biometrika 63, 581-592.
22. Casella, G. and Berger, R. L. (2002). Statistical Inference. Duxbury Press.
23. Koenker, R. and Bassett, G. (1978). Regression quantiles. Econometrica 46, 33-50.
24. Koenker, R., Ng, P., and Portnoy S. (1994). Quantile smoothing splines.Biometrika 81, 673-680.
25. Bottai, M., Cai, B., and McKeown, R. (2010). Logistic quantile regression. Statistics in Medicine 29, 309-317.
26. Mu, Y. and He, X. (2007). Power transformation toward a linear regression quantile. JASA 102, 269-279.
27. Jung, S. (1996). Quasi-likelihood for median regression models. Journal of the American Statistical Association 91, 251-257.
28. Lipsitz, S. R., Fitzmaurice, G. M., Molenberghs, G., and Zhao, L. P. (1997). Quantile regression methods for longitudinal data with drop-outs: application to cd4 cell counts of patients infected with the human immunodeficiency virus. Journal of the Royal Statistical Society, Series C: Applied Statistics 46, 463-476.
29. Geraci, M. and Bottai, M. (2007). Quantile regression for longitudinal data using the asymmetric laplace distribution. Biostatistics 8, 140-154.
30. Reich, B., Bondell, H., and Wang, H. (2010). Flexible bayesian quantile regression for independent and clustered data. Biostatistics page 11 (2): 337-352.
31. Powell, J. (1986). Censored quantile regression. Journal of Econometrics 32, 143-155.
32. Portnoy, S. (2003). Censored regression quantiles. Journal of the American Statistical Association 98, 1001-1012.
33. Peng, L. and Huang, Y. (2008). Survival analysis with quantile regressionmodels. Journal of the American Statistical Association 103, 637-649.
34. Bottai, M. and Zhang, J. (2010). Laplace regression with censored data. Biometrical Journal 52, 487-503.
35. Machado, J. A. F. and Santos-Silva, J. M. C. (2005). Quantiles for counts. Journal of the American Statistical Association 100, 1226-1237.
36. van Buuren, S., Boshuizen, H., and Knook, D. (1999). Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in medicine 18, 681-694.
37. Gifi, A. (1990). Nonlinear multivariate analysis. Wiley, New York.
38. Koenker, R. (2005). Quantile Regression. Cambridge University Press.
39. Raghunathan, 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. Survey Methodology 27, 85-95.
40. R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
41. van Buuren, S. and Groothuis-Oudshoorn, K. (2010). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, forthcoming .
42. Caspersen, C. J., Powell, K. E., and Christenson, G. M. (1985). Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep 100, 126-131.