Partial Parallelism Plots
Demonstrating parallelism in quantitative laboratory tests is crucial to ensure accurate reporting of data and minimise risks to patients. Regulatory authorities make the demonstration of parallelism before clinical use approval mandate. However, achieving statistical parallelism can be arduous, esp...
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Format: | Article |
Language: | English |
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MDPI AG
2024-01-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/14/2/602 |
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author | Axel Petzold |
author_facet | Axel Petzold |
author_sort | Axel Petzold |
collection | DOAJ |
description | Demonstrating parallelism in quantitative laboratory tests is crucial to ensure accurate reporting of data and minimise risks to patients. Regulatory authorities make the demonstration of parallelism before clinical use approval mandate. However, achieving statistical parallelism can be arduous, especially when parallelism is limited to a subrange of the data. To address potential biases and confounds, I propose a simple graphical method, the Partial Parallelism Plot, to demonstrate partial parallelism. The proposed method offers ease of understanding, intuitiveness, and graphical simplicity. It enables the graphical assessment of quantitative data risk when parallelism is lacking within a defined range. As parallelism may not be consistent across the entire analytical range, the plots focus on partial parallelism. The method can readily be programmed into graphical applications for enhanced interactivity. By providing a clear graphical representation, the method allows researchers to ascertain the presence of parallelism in laboratory tests, thus aiding in the validation process for trials and clinical applications. |
first_indexed | 2024-03-08T09:59:05Z |
format | Article |
id | doaj.art-a9f46de52b934deca5a1f56e15af70cb |
institution | Directory Open Access Journal |
issn | 2076-3417 |
language | English |
last_indexed | 2024-03-08T09:59:05Z |
publishDate | 2024-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Applied Sciences |
spelling | doaj.art-a9f46de52b934deca5a1f56e15af70cb2024-01-29T13:43:01ZengMDPI AGApplied Sciences2076-34172024-01-0114260210.3390/app14020602Partial Parallelism PlotsAxel Petzold0Queen Square Institute of Neurology, UCL, London WC1N 3BG, UKDemonstrating parallelism in quantitative laboratory tests is crucial to ensure accurate reporting of data and minimise risks to patients. Regulatory authorities make the demonstration of parallelism before clinical use approval mandate. However, achieving statistical parallelism can be arduous, especially when parallelism is limited to a subrange of the data. To address potential biases and confounds, I propose a simple graphical method, the Partial Parallelism Plot, to demonstrate partial parallelism. The proposed method offers ease of understanding, intuitiveness, and graphical simplicity. It enables the graphical assessment of quantitative data risk when parallelism is lacking within a defined range. As parallelism may not be consistent across the entire analytical range, the plots focus on partial parallelism. The method can readily be programmed into graphical applications for enhanced interactivity. By providing a clear graphical representation, the method allows researchers to ascertain the presence of parallelism in laboratory tests, thus aiding in the validation process for trials and clinical applications.https://www.mdpi.com/2076-3417/14/2/602parallelismbiomarkerlaboratorytestgraphical statistics |
spellingShingle | Axel Petzold Partial Parallelism Plots Applied Sciences parallelism biomarker laboratory test graphical statistics |
title | Partial Parallelism Plots |
title_full | Partial Parallelism Plots |
title_fullStr | Partial Parallelism Plots |
title_full_unstemmed | Partial Parallelism Plots |
title_short | Partial Parallelism Plots |
title_sort | partial parallelism plots |
topic | parallelism biomarker laboratory test graphical statistics |
url | https://www.mdpi.com/2076-3417/14/2/602 |
work_keys_str_mv | AT axelpetzold partialparallelismplots |