Inverse probability weighted Cox regression for doubly truncated data
نویسندگان
چکیده
منابع مشابه
Analysis of Dependently Truncated Sample Using Inverse Probability Weighted Estimator
Many statistical methods for truncated data rely on the assumption that the failure and truncation time are independent, which can be unrealistic in applications. The study cohorts obtained from bone marrow transplant (BMT) registry data are commonly recognized as truncated samples, the time-to-failure is truncated by the transplant time. There are clinical evidences that a longer transplant wa...
متن کاملInverse-Probability-Weighted Estimation for Monotone and Nonmonotone Missing Data.
Missing data is a common occurrence in epidemiologic research. In this paper, 3 data sets with induced missing values from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are provided as examples of prototypical epidemiologic studies with missing data. Our goal was to estimate the association of maternal smoking behavior with spontaneous abortion while adj...
متن کاملBootstrapping the NPMLE for doubly truncated data
986812401 Doubly truncated data appear in a number of applications, including astronomy and survival analysis. In this paper we review the existing methods to compute the NPMLE under double truncation, which has no explicit form and must be approximated numerically. We introduce the bootstrap as a method to estimate the finite sample distribution of the NPMLE under double truncation. The perfor...
متن کاملDoubly regularized Cox regression for high-dimensional survival data with group structures
The goal of this research is to integrate group structures to the Cox proportional hazards model with ultra highdimensional predictors. By doubly regularizing the partial likelihood based on the Cox model with convex penalties, this method is able to perform group selection and withingroup selection simultaneously. Compared with methods ignoring the structure information, our method yields bett...
متن کاملNonparametric analysis of doubly truncated data
One of the principal goals of the quasar investigations is to study luminosity evolution. A convenient one-parameter model for luminosity says that the expected log luminosity, T ∗, increases linearly as θ0 · log(1+ Z∗), and T ∗(θ0) = T ∗ − θ0 · log(1 + Z∗) is independent of Z∗, where Z∗ is the redshift of a quasar and θ0 is the true value of evolution parameter. Due to experimental constraints...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biometrics
سال: 2017
ISSN: 0006-341X
DOI: 10.1111/biom.12771