Cargando…
Sensitivity analysis of selection bias: a graphical display by bias-correction index
BACKGROUND: In observational studies, how the magnitude of potential selection bias in a sensitivity analysis can be quantified is rarely discussed. The purpose of this study was to develop a sensitivity analysis strategy by using the bias-correction index (BCI) approach for quantifying the influenc...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657564/ https://www.ncbi.nlm.nih.gov/pubmed/38025739 http://dx.doi.org/10.7717/peerj.16411 |
_version_ | 1785148175282077696 |
---|---|
author | Chung, Ping-Chen Lin, I-Feng |
author_facet | Chung, Ping-Chen Lin, I-Feng |
author_sort | Chung, Ping-Chen |
collection | PubMed |
description | BACKGROUND: In observational studies, how the magnitude of potential selection bias in a sensitivity analysis can be quantified is rarely discussed. The purpose of this study was to develop a sensitivity analysis strategy by using the bias-correction index (BCI) approach for quantifying the influence and direction of selection bias. METHODS: We used a BCI, a function of selection probabilities conditional on outcome and covariates, with different selection bias scenarios in a logistic regression setting. A bias-correction sensitivity plot was illustrated to analyze the associations between proctoscopy examination and sociodemographic variables obtained using the data from the Taiwan National Health Interview Survey (NHIS) and of a subset of individuals who consented to having their health insurance data further linked. RESULTS: We included 15,247 people aged ≥20 years, and 87.74% of whom signed the informed consent. When the entire sample was considered, smokers were less likely to undergo proctoscopic examination (odds ratio (OR): 0.69, 95% CI [0.57–0.84]), than nonsmokers were. When the data of only the people who provided consent were considered, the OR was 0.76 (95% CI [0.62–0.94]). The bias-correction sensitivity plot indicated varying ORs under different degrees of selection bias. CONCLUSIONS: When data are only available in a subsample of a population, a bias-correction sensitivity plot can be used to easily visualize varying ORs under different selection bias scenarios. The similar strategy can be applied to models other than logistic regression if an appropriate BCI is derived. |
format | Online Article Text |
id | pubmed-10657564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106575642023-11-16 Sensitivity analysis of selection bias: a graphical display by bias-correction index Chung, Ping-Chen Lin, I-Feng PeerJ Epidemiology BACKGROUND: In observational studies, how the magnitude of potential selection bias in a sensitivity analysis can be quantified is rarely discussed. The purpose of this study was to develop a sensitivity analysis strategy by using the bias-correction index (BCI) approach for quantifying the influence and direction of selection bias. METHODS: We used a BCI, a function of selection probabilities conditional on outcome and covariates, with different selection bias scenarios in a logistic regression setting. A bias-correction sensitivity plot was illustrated to analyze the associations between proctoscopy examination and sociodemographic variables obtained using the data from the Taiwan National Health Interview Survey (NHIS) and of a subset of individuals who consented to having their health insurance data further linked. RESULTS: We included 15,247 people aged ≥20 years, and 87.74% of whom signed the informed consent. When the entire sample was considered, smokers were less likely to undergo proctoscopic examination (odds ratio (OR): 0.69, 95% CI [0.57–0.84]), than nonsmokers were. When the data of only the people who provided consent were considered, the OR was 0.76 (95% CI [0.62–0.94]). The bias-correction sensitivity plot indicated varying ORs under different degrees of selection bias. CONCLUSIONS: When data are only available in a subsample of a population, a bias-correction sensitivity plot can be used to easily visualize varying ORs under different selection bias scenarios. The similar strategy can be applied to models other than logistic regression if an appropriate BCI is derived. PeerJ Inc. 2023-11-16 /pmc/articles/PMC10657564/ /pubmed/38025739 http://dx.doi.org/10.7717/peerj.16411 Text en ©2023 Chung and Lin https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Epidemiology Chung, Ping-Chen Lin, I-Feng Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title | Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title_full | Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title_fullStr | Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title_full_unstemmed | Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title_short | Sensitivity analysis of selection bias: a graphical display by bias-correction index |
title_sort | sensitivity analysis of selection bias: a graphical display by bias-correction index |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657564/ https://www.ncbi.nlm.nih.gov/pubmed/38025739 http://dx.doi.org/10.7717/peerj.16411 |
work_keys_str_mv | AT chungpingchen sensitivityanalysisofselectionbiasagraphicaldisplaybybiascorrectionindex AT linifeng sensitivityanalysisofselectionbiasagraphicaldisplaybybiascorrectionindex |