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Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines
Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632483/ https://www.ncbi.nlm.nih.gov/pubmed/29312462 http://dx.doi.org/10.1155/2017/7518035 |
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author | Malloy, Elizabeth J. Kapellusch, Jay M. Garg, Arun |
author_facet | Malloy, Elizabeth J. Kapellusch, Jay M. Garg, Arun |
author_sort | Malloy, Elizabeth J. |
collection | PubMed |
description | Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data set under a known exposure-response relationship and in a data application examining risk of carpal tunnel syndrome in an occupational cohort. |
format | Online Article Text |
id | pubmed-5632483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-56324832018-01-08 Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines Malloy, Elizabeth J. Kapellusch, Jay M. Garg, Arun Comput Math Methods Med Research Article Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data set under a known exposure-response relationship and in a data application examining risk of carpal tunnel syndrome in an occupational cohort. Hindawi 2017 2017-09-20 /pmc/articles/PMC5632483/ /pubmed/29312462 http://dx.doi.org/10.1155/2017/7518035 Text en Copyright © 2017 Elizabeth J. Malloy et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Malloy, Elizabeth J. Kapellusch, Jay M. Garg, Arun Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title | Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title_full | Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title_fullStr | Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title_full_unstemmed | Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title_short | Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines |
title_sort | estimating and interpreting effects from nonlinear exposure-response curves in occupational cohorts using truncated power basis expansions and penalized splines |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632483/ https://www.ncbi.nlm.nih.gov/pubmed/29312462 http://dx.doi.org/10.1155/2017/7518035 |
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