Estimating and interpreting effects from nonlinear exposure-response curves in occupational cohorts using truncated power basis expansions and penalized splines

DOI10.1155/2017/7518035zbMath1395.62306OpenAlexW2756418603WikidataQ47193922 ScholiaQ47193922MaRDI QIDQ1664536

Arun Garg, Jay M. Kapellusch, Elisabeth J. Malloy

Publication date: 27 August 2018

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/7518035

Mathematics Subject Classification ID

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

Uses Software

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• survival
• SemiPar
• SmoothHR

Cites Work

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• Comparing measures of model selection for penalized splines in Cox models
• A practical guide to splines
• Modeling survival data: extending the Cox model
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• SmoothHR: an R package for pointwise nonparametric estimation of hazard ratio curves of continuous predictors
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Semiparametric Regression
• Determination of the functional form of the relationship of covariates to the log hazard ratio in a Cox model

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