How to deal with non-detectable and outlying values in biomarker research: Best practices and recommendations for univariate imputation approaches.

ABSTRACT: Non-detectable (ND) and outlying concentration values (OV) are a common challenge of biomarker investigations. However, best practices on how to aptly deal with the affected cases are still missing. The high methodological heterogeneity in biomarker-oriented research, as for example, in the field of psychoneuroendocrinology, and the statistical bias in some of the applied methods may compromise the robustness, comparability, and generalizability of research findings. In this paper, we describe the occurrence of ND and OV in terms of a model that considers them as censored data, for instance due to measurement error cutoffs. We then present common univariate approaches in handling ND and OV by highlighting their respective strengths and drawbacks. In a simulation study with lognormal distri

SUBMITTER: Herbers J 

PROVIDER: S-EPMC9216349 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature