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The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies
BACKGROUND: Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers struggle with the interpretation of lift. As a result, dissemination of data min...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580490/ https://www.ncbi.nlm.nih.gov/pubmed/31208407 http://dx.doi.org/10.1186/s12911-019-0838-4 |
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author | Vu, Khanh Clark, Rebecca A. Bellinger, Colin Erickson, Graham Osornio-Vargas, Alvaro Zaïane, Osmar R. Yuan, Yan |
author_facet | Vu, Khanh Clark, Rebecca A. Bellinger, Colin Erickson, Graham Osornio-Vargas, Alvaro Zaïane, Osmar R. Yuan, Yan |
author_sort | Vu, Khanh |
collection | PubMed |
description | BACKGROUND: Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers struggle with the interpretation of lift. As a result, dissemination of data mining results can be met with hesitation. The relative risk and odds ratio are standard association measures in the health domain, due to their straightforward interpretation and comparability across populations. We aimed to investigate the lift-relative risk and the lift-odds ratio relationships, and provide tools to convert lift to the relative risk and odds ratio. METHODS: We derived equations linking lift-relative risk and lift-odds ratio. We discussed how lift, relative risk, and odds ratio behave numerically with varying association strengths and exposure prevalence levels. The lift-relative risk relationship was further illustrated using a high-dimensional dataset which examines the association of exposure to airborne pollutants and adverse birth outcomes. We conducted spatial association rule mining using the Kingfisher algorithm, which identified association rules using its built-in lift metric. We directly estimated relative risks and odds ratios from 2 by 2 tables for each identified rule. These values were compared to the corresponding lift values, and relative risks and odds ratios were computed using the derived equations. RESULTS: As the exposure-outcome association strengthens, the odds ratio and relative risk move away from 1 faster numerically than lift, i.e. |log (odds ratio)| ≥ |log (relative risk)| ≥ |log (lift)|. In addition, lift is bounded by the smaller of the inverse probability of outcome or exposure, i.e. lift≤ min (1/P(O), 1/P(E)). Unlike the relative risk and odds ratio, lift depends on the exposure prevalence for fixed outcomes. For example, when an exposure A and a less prevalent exposure B have the same relative risk for an outcome, exposure A has a lower lift than B. CONCLUSIONS: Lift, relative risk, and odds ratio are positively correlated and share the same null value. However, lift depends on the exposure prevalence, and thus is not straightforward to interpret or to use to compare association strength. Tools are provided to obtain the relative risk and odds ratio from lift. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0838-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6580490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65804902019-06-24 The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies Vu, Khanh Clark, Rebecca A. Bellinger, Colin Erickson, Graham Osornio-Vargas, Alvaro Zaïane, Osmar R. Yuan, Yan BMC Med Inform Decis Mak Research Article BACKGROUND: Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers struggle with the interpretation of lift. As a result, dissemination of data mining results can be met with hesitation. The relative risk and odds ratio are standard association measures in the health domain, due to their straightforward interpretation and comparability across populations. We aimed to investigate the lift-relative risk and the lift-odds ratio relationships, and provide tools to convert lift to the relative risk and odds ratio. METHODS: We derived equations linking lift-relative risk and lift-odds ratio. We discussed how lift, relative risk, and odds ratio behave numerically with varying association strengths and exposure prevalence levels. The lift-relative risk relationship was further illustrated using a high-dimensional dataset which examines the association of exposure to airborne pollutants and adverse birth outcomes. We conducted spatial association rule mining using the Kingfisher algorithm, which identified association rules using its built-in lift metric. We directly estimated relative risks and odds ratios from 2 by 2 tables for each identified rule. These values were compared to the corresponding lift values, and relative risks and odds ratios were computed using the derived equations. RESULTS: As the exposure-outcome association strengthens, the odds ratio and relative risk move away from 1 faster numerically than lift, i.e. |log (odds ratio)| ≥ |log (relative risk)| ≥ |log (lift)|. In addition, lift is bounded by the smaller of the inverse probability of outcome or exposure, i.e. lift≤ min (1/P(O), 1/P(E)). Unlike the relative risk and odds ratio, lift depends on the exposure prevalence for fixed outcomes. For example, when an exposure A and a less prevalent exposure B have the same relative risk for an outcome, exposure A has a lower lift than B. CONCLUSIONS: Lift, relative risk, and odds ratio are positively correlated and share the same null value. However, lift depends on the exposure prevalence, and thus is not straightforward to interpret or to use to compare association strength. Tools are provided to obtain the relative risk and odds ratio from lift. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0838-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-17 /pmc/articles/PMC6580490/ /pubmed/31208407 http://dx.doi.org/10.1186/s12911-019-0838-4 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Vu, Khanh Clark, Rebecca A. Bellinger, Colin Erickson, Graham Osornio-Vargas, Alvaro Zaïane, Osmar R. Yuan, Yan The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title | The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title_full | The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title_fullStr | The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title_full_unstemmed | The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title_short | The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
title_sort | index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580490/ https://www.ncbi.nlm.nih.gov/pubmed/31208407 http://dx.doi.org/10.1186/s12911-019-0838-4 |
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