Albert, Carlo, Vogel, Sören and Ashauer, Roman orcid.org/0000-0002-9579-8793 (2016) Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS). PLoS Computational Biology. e1004978. pp. 1-19. ISSN 1553-734X
Abstract
The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Environment and Geography (York) |
Depositing User: | Pure (York) |
Date Deposited: | 01 Aug 2016 14:20 |
Last Modified: | 16 Oct 2024 13:11 |
Published Version: | https://doi.org/10.1371/journal.pcbi.1004978 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1371/journal.pcbi.1004978 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103211 |