Sieve estimation of a class of partially linear transformation models with interval-censored competing risks data.

ABSTRACT: In this paper, we consider a class of partially linear transformation models with interval-censored competing risks data. Under a semiparametric generalized odds rate specification for the cause-specific cumulative incidence function, we obtain optimal estimators of the large number of parametric and nonparametric model components via maximizing the likelihood function over a joint B-spline and Bernstein polynomial spanned sieve space. Our specification considers a relatively simpler finite-dimensional parameter space, approximating the infinite-dimensional parameter space as n → ∞, thereby allowing us to study the almost sure consistency, and rate of convergence for all parameters, and the asymptotic distributions and efficiency of the finite-dimensional components. We study the fi

SUBMITTER: Lu X 

PROVIDER: S-EPMC10208244 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature