Dimension reduction in the linear model for right-censored data: Predicting the change of HIV-I RNA levels using clinical and Protease gene mutation data

DOI10.1007/S10985-004-4776-8zbMath1058.62101OpenAlexW1979635159WikidataQ30982035 ScholiaQ30982035MaRDI QIDQ1770871

Xianqiang Yang

Publication date: 7 April 2005

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10985-004-4776-8

zbMATH Keywords

partial least squaresdimension reductioncross-validationfailure time model

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01)

Cites Work

• Random-Effects Models for Longitudinal Data
• Estimating regression parameters using linear rank tests for censored data
• The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
• On the structure of partial least squares regression
• Linear regression with censored data
• A Biometrics Invited Paper. The Analysis and Selection of Variables in Linear Regression
• Rank-based inference for the accelerated failure time model
• 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
• Iterative Partial Least Squares with Right‐Censored Data Analysis: A Comparison to Other Dimension Reduction Techniques

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