Semiparametric sieve maximum likelihood estimation for accelerated hazards model with interval-censored data

DOI10.1016/J.JSPI.2019.07.002zbMath1437.62622OpenAlexW2964342574MaRDI QIDQ2301055

Xiaoyu Liu, Liming Xiang, Zsolt Szabó

Publication date: 28 February 2020

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2019.07.002

zbMATH Keywords

splinesasymptoticsinterval censoringaccelerated hazards modelsieve maximum likelihood

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (2)

Link-based survival additive models under mixed censoring to assess risks of hospital-acquired infections ⋮ Generalized accelerated hazards mixture cure models with interval-censored data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Convergence rate of sieve estimates
• Partially linear transformation cure models for interval-censored data
• Weak convergence and empirical processes. With applications to statistics
• Induced smoothing for the semiparametric accelerated hazards model
• Efficient estimation for semiparametric cure models with interval-censored data
• The statistical analysis of interval-censored failure time data.
• A New Semiparametric Estimation Method for Accelerated Hazard Model
• A Spline-Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval-Censored Data
• Accelerated Hazards Regression Model and Its Adequacy for Censored Survival Data
• Sieve maximum likelihood regression analysis of dependent current status data
• “Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data
• Interval censoring: identifiability and the constant-sum property
• Asymptotic Statistics
• Hazard Function Estimation Using B-Splines
• Sieve Estimation for the Proportional-Odds Failure-Time Regression Model With Interval Censoring
• Analysis of Accelerated Hazards Models
• Interval censoring: Model characterizations for the validity of the simplified likelihood
• Accelerated hazards model based on parametric families generalized with Bernstein polynomials
• Estimation of the mean function with panel count data using monotone polynomial splines
• Data Envelope Fitting with Constrained Polynomial Splines

This page was built for publication: Semiparametric sieve maximum likelihood estimation for accelerated hazards model with interval-censored data