Estimating time-varying treatment switching effects via local linear smoothing and quasi-likelihood

DOI10.1016/J.CSDA.2016.12.012zbMath1466.62137OpenAlexW2568640390MaRDI QIDQ1658415

Wenchao Xu, Yuedong Wang, Hongmei Lin, Ri-quan Zhang

Publication date: 14 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2016.12.012

zbMATH Keywords

local linear smoothinghospitalizationlocal quasi-likelihoodbranching curveshaemodialysis

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (1)

Estimating time-varying treatment switching effect using accelerated failure time model with application to vascular access for hemodialysis

Cites Work

• Unnamed Item
• Longitudinal data with follow-up truncated by death: match the analysis method to research aims
• Functional single index models for longitudinal data
• Bandwidth selection for smooth backfitting in additive models
• Cardiovascular event risk dynamics over time in older patients on dialysis: A generalized multiple-index varying coefficient model approach
• Penalized Clustering of Large-Scale Functional Data With Multiple Covariates
• The Nonparametric Estimation of Branching Curves
• The Performance of Cross-Validation and Maximum Likelihood Estimators of Spline Smoothing Parameters
• Generalized Partially Linear Single-Index Models
• Efficient Estimation and Inferences for Varying-Coefficient Models

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