Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi.

We found that the choice of imputation strategy exerted significant influence over both scores and associated ranks, and the most sensitive scenarios were those involving fewer assays plus higher proportions of missing data. By characterizing the effects of missing data and the relative benefit of imputation approaches across real-world data scenarios, we can augment confidence in the robustness of decisions regarding the health and ecological effects of environmental chemicals.