Dichotomization is often used on clinical and diagnostic settings to simplify interpretation. For example, a person with systolic and diastolic blood pressure above 140 over 90 may be prescribed medication. Blood pressure as well as other factors such as age and cholesterol and their interactions may lead to increased risk of certain diseases. When using a dichotomized variable to determine a diagnosis, if the interactions with other variables are not considered, then an incorrect threshold for the continuous variable may be selected. In this paper, we compare single dichotomization with joint dichotomization; the process of simultaneously optimizing cutpoints for multiple variables. A simulation study shows that simultaneous dichotomization of continuous variables is more accurate in recovering both ‘true’ thresholds given they exist.
Funding source: South Carolina Clinical and Translational Research Institute, Medical University of South Carolina’s CTSA, NIH/NCATS
Award Identifier / Grant number: UL1TR000062
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This project was supported in part by the South Carolina Clinical and Translational Research Institute, Medical University of South Carolina’s CTSA, NIH/NCATS Grant Number UL1TR000062.
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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The online version of this article offers supplementary material (https://doi.org/10.1515/ijb-2021-0071).
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