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. 2014 Jul;9(7):1328-35.
doi: 10.2215/CJN.10141013. Epub 2014 Feb 7.

Addressing missing data in clinical studies of kidney diseases

Maria E Montez-Rath  1 , Wolfgang C Winkelmayer  2 , Manisha Desai  3
Affiliations

Addressing missing data in clinical studies of kidney diseases

Maria E Montez-Rath et al. Clin J Am Soc Nephrol. 2014 Jul.

Abstract

Missing data constitute a problem present in all studies of medical research. The most common approach to handling missing data-complete case analysis-relies on assumptions about missing data that rarely hold in practice. The implications of this approach are biased and inefficient descriptions of relationships of interest. Here, various approaches for handling missing data in clinical studies are described. In particular, this work promotes the use of multiple imputation methods that rely on assumptions about missingness that are more flexible than those assumptions relied on by the most common method in use. Furthermore, multiple imputation methods are becoming increasingly more accessible in mainstream statistical software packages, making them both a sound and practical choice. The use of multiple imputation methods is illustrated with examples pertinent to kidney research, and concrete guidance on their use is provided.

Keywords: biostatistics; epidemiology and outcomes; outcomes.

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Figures

Figure 1.
Figure 1.
Trajectories of eGFR measurements for hypothetical study of kidney transplant patients followed longitudinally. Three eGFR trajectories are shown: the true trajectory, the trajectory estimated based on observed measurements, and the trajectory estimated on both observed measurements and measurements assuming the last eGFR value for those patients who did not return to the clinic.
Figure 2.
Figure 2.
Missing data mechanisms. MAR, missing at random; MCAR, missing completely at random; NMAR, not missing at random.
Figure 3.
Figure 3.
Illustrative flow chart of implementation of multiple imputation when linear regression is of interest and five imputations are performed.
See this image and copyright information in PMC

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