London, December 14, 2019

Column 1

The presentation

Please find here the presentation and the archive with the files that generated the presentation.

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References

The following sources are referred to [in order of appearance]

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  • Schafer, J. (1997). Analysis of incomplete multivariate data. Chapman & Hall/CRC.
  • Van Ginkel, J. R., Van der Ark, L. A., and Sijtsma, K. (2007). Multiple imputation for item scores when test data are factorially complex. British Journal of Mathematical and Statistical Psychology, 60(2):315–338.
  • Goldstein, H., Carpenter, J., Kenward, M. G., and Levin, K. A. (2009). Multilevel models with multivariate mixed response types. Statistical Modelling, 9(3):173–197.
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  • Demirtas, H., Freels, S. A., and Yucel, R. M. (2008). Plausibility of multivariate normality assumption when multiply imputing non-gaussian continuous outcomes: a simulation assessment. Journal of Statistical Computation and Simulation, 78(1):69–84.
  • Kennickell, A. B. (1991). Imputation of the 1989 survey of consumer finances: Stochastic relaxation and multiple imputation. Technical report, mimeo, Board of Governors of the Federal Reserve System.
  • Oudshoorn, C. G. M., Buuren, S., and Rijckevorsel, J. L. A. (1999). Flexible multiple imputation by chained equations of the AVO-95 survey. TNO Prevention and Health Leiden.
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  • Van Buuren, S. and Oudshoorn, C. (2000). Multivariate imputation by chained equations: Mice v1. 0 user’s manual. The Netherlands: TNO Report PG/VGZ/00.038. Netherlands Organization for applied scientific research.
  • 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(1):85–96.
  • Faris, P. D., Ghali, W. A., Brant, R., Norris, C. M., Galbraith, P. D., and Knudtson, M. L. (2002). Multiple imputation versus data enhancement for dealing with missing data in observational health care outcome analyses. Journal of Clinical Epidemiology, 55(2):184–191.
  • Van Buuren, S., Brand, J. P., Groothuis-Oudshoorn, C., and Rubin, D. B. (2006). Fully conditional specification in multivariate imputation. Journal of statistical computation and simulation, 76(12):1049–1064.
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  • Lee, K. J. and Carlin, J. B. (2010). Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation. American Journal of Epidemiology, 171(5):624–632.
  • Snijders, T. A. B., and R. J. Bosker. 2012. Multilevel Analysis. an Introduction to Basic and Advanced Multilevel Modeling. Second Edition. London: Sage Publications Ltd.
  • Zhu, J. 2016. “Assessment and Improvement of a Sequential Regression Multivariate Imputation Algorithm.” PhD thesis, University of Michigan.