Quantile Regression For Longitudinal Biomarker Data Subject to Left Censoring and Dropouts
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Publication:5172824
DOI10.1080/03610926.2012.729641zbMath1305.62371OpenAlexW2026799940MaRDI QIDQ5172824
Publication date: 5 February 2015
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2012.729641
Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Censored data models (62N01)
Related Items (2)
Quantile regression modeling of latent trajectory features with longitudinal data ⋮ Quantile regression analysis of censored longitudinal data with irregular outcome-dependent follow-up
Cites Work
- Inference for censored quantile regression models in longitudinal studies
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- Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression
- Quantile Regression Methods for Longitudinal Data with Drop-outs: Application to CD4 Cell Counts of Patients Infected with the Human Immunodeficiency Virus
- A Joint Model for Nonlinear Mixed-Effects Models With Censoring and Covariates Measured With Error, With Application to AIDS Studies
- Random Regression Models for Human Immunodeficiency Virus Ribonucleic Acid Data Subject to Left Censoring and Informative Drop-Outs
- Mixed Effects Models with Censored Data with Application to HIV RNA Levels
- Analysis of left-censored longitudinal data with application to viral load in HIV infection
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