Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package.
With the growing concerns about research reproducibility and replicability, the assessment of scientific results' fragility (or robustness) has been of increasing interest. The fragility index was proposed to quantify the robustness of statistical significance of clinical studies with binary ou...
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0268754&type=printable |
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| author | Lifeng Lin Haitao Chu |
| author_facet | Lifeng Lin Haitao Chu |
| author_sort | Lifeng Lin |
| collection | DOAJ |
| description | With the growing concerns about research reproducibility and replicability, the assessment of scientific results' fragility (or robustness) has been of increasing interest. The fragility index was proposed to quantify the robustness of statistical significance of clinical studies with binary outcomes. It is defined as the minimal event status modifications that can alter statistical significance. It helps clinicians evaluate the reliability of the conclusions. Many factors may affect the fragility index, including the treatment groups in which event status is modified, the statistical methods used for testing for the association between treatments and outcomes, and the pre-specified significance level. In addition to assessing the fragility of individual studies, the fragility index was recently extended to both conventional pairwise meta-analyses and network meta-analyses of multiple treatment comparisons. It is not straightforward for clinicians to calculate these measures and visualize the results. We have developed an R package called "fragility" to offer user-friendly functions for such purposes. This article provides an overview of methods for assessing and visualizing the fragility of individual studies as well as pairwise and network meta-analyses, introduces the usage of the "fragility" package, and illustrates the implementations with several worked examples. |
| format | Article |
| id | doaj-art-615448d0fad344d28986d1449509a5a1 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-615448d0fad344d28986d1449509a5a12025-01-24T05:31:11ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01176e026875410.1371/journal.pone.0268754Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package.Lifeng LinHaitao ChuWith the growing concerns about research reproducibility and replicability, the assessment of scientific results' fragility (or robustness) has been of increasing interest. The fragility index was proposed to quantify the robustness of statistical significance of clinical studies with binary outcomes. It is defined as the minimal event status modifications that can alter statistical significance. It helps clinicians evaluate the reliability of the conclusions. Many factors may affect the fragility index, including the treatment groups in which event status is modified, the statistical methods used for testing for the association between treatments and outcomes, and the pre-specified significance level. In addition to assessing the fragility of individual studies, the fragility index was recently extended to both conventional pairwise meta-analyses and network meta-analyses of multiple treatment comparisons. It is not straightforward for clinicians to calculate these measures and visualize the results. We have developed an R package called "fragility" to offer user-friendly functions for such purposes. This article provides an overview of methods for assessing and visualizing the fragility of individual studies as well as pairwise and network meta-analyses, introduces the usage of the "fragility" package, and illustrates the implementations with several worked examples.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0268754&type=printable |
| spellingShingle | Lifeng Lin Haitao Chu Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. PLoS ONE |
| title | Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. |
| title_full | Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. |
| title_fullStr | Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. |
| title_full_unstemmed | Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. |
| title_short | Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package. |
| title_sort | assessing and visualizing fragility of clinical results with binary outcomes in r using the fragility package |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0268754&type=printable |
| work_keys_str_mv | AT lifenglin assessingandvisualizingfragilityofclinicalresultswithbinaryoutcomesinrusingthefragilitypackage AT haitaochu assessingandvisualizingfragilityofclinicalresultswithbinaryoutcomesinrusingthefragilitypackage |