The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model
Open accessAbstract
Missing covariate data commonly occur in epidemiological and clinical research, and are often dealt with using multiple imputation. Imputation of partially observed covariates is complicated if the substantive model is non-linear (e.g. Cox proportional hazards model), or contains non-linear (e.g. squared) or interaction terms, and standard software implementations of multiple imputation may impute covariates from models that are incompatible with such substantive models. We show how imputation by fully conditional specification, a popular approach for performing multiple imputation, can be modified so that covariates are imputed from models which are compatible with the substantive model. We investigate through simulation the performance of this proposal, and compare it with existing approaches. Simulation results suggest our proposal gives consistent estimates for a range of common substantive models, including models which contain non-linear covariate effects or interactions, provided data are missing at random and the assumed imputation models are correctly specified and mutually compatible. Stata software implementing the approach is freely available.
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Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Multiple imputation using chained equations: Issues and guidance for practice
White, I. R., Royston, P., & Wood, A. M. (2011) · Statistics in Medicine · doi:10.1002/sim.4067 · Cited by 9,792
Self-citationAnalysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012
Multiple imputation of discrete and continuous data by fully conditional specification
van Buuren, S. (2007) · Statistical Methods in Medical Research · doi:10.1177/0962280206074463 · Cited by 2,827
Flexible Imputation of Missing Data
van Buuren, S. (2012) · doi:10.1201/b11826 · Cited by 2,022
Fully conditional specification in multivariate imputation
Van Buuren, S., Brand, J. P. L., Groothuis-Oudshoorn, C. G. M., & Rubin, D. B. (2006) · Journal of Statistical Computation and Simulation · doi:10.1080/10629360600810434 · Cited by 1,217
Cited by
Tuning multiple imputation by predictive mean matching and local residual draws
Morris, T. P., White, I. R., & Royston, P. (2014) · BMC Medical Research Methodology · doi:10.1186/1471-2288-14-75 · Cited by 568
Self-citationMultiple Imputation of Missing Data for Multilevel Models: Simulations and Recommendations
Grund, S., Lüdtke, O., & Robitzsch, A. (2018) · Organizational Research Methods · doi:10.1177/1094428117703686 · Cited by 224
Missing data: A statistical framework for practice
Carpenter, J. R., & Smuk, M. (2021) · Biometrical Journal · doi:10.1002/bimj.202000196 · Cited by 198
Self-citationEnders, C. K., Du, H., & Keller, B. T. (2020) · Psychological Methods · doi:10.1037/met0000228 · Cited by 166
Major Depression and Survival in People With Cancer
Walker, J., Mulick, A., Magill, N., Symeonides, S., Gourley, C., Burke, K., Belot, A., Quartagno, M., van Niekerk, M., Toynbee, M., et al. (2021) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000942 · Cited by 124
Metadata
- Authors
- Bartlett, J. W., Seaman, S. R., White, I. R., Carpenter, J. R., & Initiative*, F. T. A. D. N.
- Venue
- Statistical Methods in Medical Research
- Publisher
- SAGE Publications
- Published
- 2014-02-12
- Volume
- 24
- Issue
- 4
- Pages
- 462-487
- ISSN
- 0962-2802 (ISSN-L)
- 1477-0334
- OpenAlex
- W2157235443
- Cited by
- 485
- References
- 7
- FWCI
- 22.34
- Type
- journal article
- Language
- en
- Open access
- hybrid
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