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Comment
. 2024 Jan;66(1):e2300085.
doi: 10.1002/bimj.202300085. Epub 2023 Oct 12.

Comment on Oberman & Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?

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Comment

Comment on Oberman & Vink: Should we fix or simulate the complete data in simulation studies evaluating missing data methods?

Tim P Morris et al. Biom J. 2024 Jan.

Abstract

For simulation studies that evaluate methods of handling missing data, we argue that generating partially observed data by fixing the complete data and repeatedly simulating the missingness indicators is a superficially attractive idea but only rarely appropriate to use.

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Conflict of interest statement

The authors declare no conflicts of interest.

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References

REFERENCES

    1. Balzer, L. B., Petersen, M. L., van der Laan, M. J., & the SEARCH Collaboration. (2016). Targeted estimation and inference for the sample average treatment effect in trials with and without pair-matching. Statistics in Medicine, 35(21), 3717-3732.
    1. Barnard, J., & Rubin, D. B. (1999). Small-sample degrees of freedom with multiple imputation. Biometrika, 86, 948-955.
    1. Brand, J. P. L., van Buuren, S., Groothuis-Oudshoorn, K., & Gelsema, E. S. (2003). A toolkit in SAS for the evaluation of multiple imputation methods. Statistica Neerlandica, 57(1), 36-45.
    1. Carpenter, J. R., & Smuk, M. (2021). Missing data: A statistical framework for practice. Biometrical Journal, 63(5), 915-947.
    1. Hughes, R. A., Sterne, J. A. C., & Tilling, K. (2016). Comparison of imputation variance estimators. Statistical Methods in Medical Research, 25(6), 2541-2557.

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