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Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach
Time‐varying covariates can be important predictors when model based predictions are considered. A Cox model that includes time‐varying covariates is usually referred to as an extended Cox model. When only right censoring is presented in the observed survival times, the conventional partial likeliho...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10107645/ https://www.ncbi.nlm.nih.gov/pubmed/36585040 http://dx.doi.org/10.1002/sim.9645 |
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author | Webb, Annabel Ma, Jun |
author_facet | Webb, Annabel Ma, Jun |
author_sort | Webb, Annabel |
collection | PubMed |
description | Time‐varying covariates can be important predictors when model based predictions are considered. A Cox model that includes time‐varying covariates is usually referred to as an extended Cox model. When only right censoring is presented in the observed survival times, the conventional partial likelihood method is still applicable to estimate the regression coefficients of an extended Cox model. However, if there are interval‐censored survival times, then the partial likelihood method is not directly available unless an imputation, such as the middle point imputation, is used to replaced the left‐ and interval‐censored data. However, such imputation methods are well known for causing biases. This paper considers fitting of the extended Cox models using the maximum penalised likelihood method allowing observed survival times to be partly interval censored, where a penalty function is used to regularise the baseline hazard estimate. We present simulation studies to demonstrate the performance of our proposed method, and illustrate our method with applications to two real datasets from medical research. |
format | Online Article Text |
id | pubmed-10107645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101076452023-04-18 Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach Webb, Annabel Ma, Jun Stat Med Research Articles Time‐varying covariates can be important predictors when model based predictions are considered. A Cox model that includes time‐varying covariates is usually referred to as an extended Cox model. When only right censoring is presented in the observed survival times, the conventional partial likelihood method is still applicable to estimate the regression coefficients of an extended Cox model. However, if there are interval‐censored survival times, then the partial likelihood method is not directly available unless an imputation, such as the middle point imputation, is used to replaced the left‐ and interval‐censored data. However, such imputation methods are well known for causing biases. This paper considers fitting of the extended Cox models using the maximum penalised likelihood method allowing observed survival times to be partly interval censored, where a penalty function is used to regularise the baseline hazard estimate. We present simulation studies to demonstrate the performance of our proposed method, and illustrate our method with applications to two real datasets from medical research. John Wiley & Sons, Inc. 2022-12-30 2023-03-15 /pmc/articles/PMC10107645/ /pubmed/36585040 http://dx.doi.org/10.1002/sim.9645 Text en © 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Webb, Annabel Ma, Jun Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title | Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title_full | Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title_fullStr | Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title_full_unstemmed | Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title_short | Cox models with time‐varying covariates and partly‐interval censoring–A maximum penalised likelihood approach |
title_sort | cox models with time‐varying covariates and partly‐interval censoring–a maximum penalised likelihood approach |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10107645/ https://www.ncbi.nlm.nih.gov/pubmed/36585040 http://dx.doi.org/10.1002/sim.9645 |
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