摘要：To study the relationship of serum antibody neutralization activity (determined by IC50) and the B cell immune response, we face two challenges: (i) IC50 values can not be observed when they are below the detected limitation, and (ii) the number of factors is larger than the number of observations. To address these two challenges, we propose a Tobit model for the analysis of the study, and an adaptive LASSO penalized variable selection procedure to identify important factors. Furthermore, we suggest extended Bayesian information criterion for selecting the tuning parameter. Our analysis indicates that three measured B cells, specifically the frequency of CD19+CD20+, CD19-CD20+, and IgD-B220-CD27- peripheral blood B cell subsets have significant effects on IC50.We have also run simulation studies to evaluate the numerical performance of the proposed method.
关键词：extended Bayesian information criterion; LASSO; penalized likelihood; high-dimensional Tobit model
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