Analysis of Heart Transplant Survival Data Using Generalized Additive Models


The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with B-splines to estimate the survival function. We model survival time… (More)
DOI: 10.1155/2013/609857


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