Making Sense of Censored Covariates: Statistical Methods for Studies of Huntington's Disease

• DOI: 10.1146/annurev-statistics-040522-095944
• Publication Date: 2023-09-08T21:04:15Z
• Authors: Sarah C. Lotspeich; Marissa C. Ashner; Jesus E. Vazquez; Brian D. Richardson; Kyle F. Grosser; Benjamin E. Bodek; Tanya P. Garcia
• Keywords: 0101 mathematics; 01 natural sciences

The landscape of survival analysis is constantly being revolutionized to answer biomedical challenges, most recently the statistical challenge censored covariates rather than outcomes. There are many promising strategies tackle covariates, including weighting, imputation, maximum likelihood, and Bayesian methods. Still, this a relatively fresh area research, different from areas outcomes (i.e., analysis) or missing covariates. In review, we discuss unique challenges encountered when handling provide an in-depth review existing methods designed address those challenges. We emphasize each method's relative strengths weaknesses, providing recommendations help investigators pinpoint best approach in their data.