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Flexible Partially Linear Single Index Regression Models For Multivariate Survival Data, Na Lei
Flexible Partially Linear Single Index Regression Models For Multivariate Survival Data, Na Lei
Electronic Thesis and Dissertation Repository
Survival regression models usually assume that covariate effects have a linear form. In many circumstances, however, the assumption of linearity may be violated. The present work addresses this limitation by adding nonlinear covariate effects to survival models. Nonlinear covariates are handled using a single index structure, which allows high-dimensional nonlinear effects to be reduced to a scalar term. The nonlinear single index approach is applied to modeling of survival data with multivariate responses, in three popular models: the proportional hazards (PH) model, the proportional odds (PO) model, and the generalized transformation model. Another extension of the PH and PO model …