Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods
<p></p><div> <p>In evidence synthesis, dealing with zero-events studies is an important and complicated task that has generated broad discussion. Numerous methods provide valid solutions to synthesizing data from studies with zero-events, either based on a frequentist or a Ba...
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2023
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| _version_ | 1864513565243736064 |
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| author | Chang Xu (102022) |
| author2 | Luis Furuya‐Kanamori (14778820) Lifeng Lin (2034385) |
| author2_role | author author |
| author_facet | Chang Xu (102022) Luis Furuya‐Kanamori (14778820) Lifeng Lin (2034385) |
| author_role | author |
| dc.creator.none.fl_str_mv | Chang Xu (102022) Luis Furuya‐Kanamori (14778820) Lifeng Lin (2034385) |
| dc.date.none.fl_str_mv | 2023-03-16T06:23:50Z |
| dc.identifier.none.fl_str_mv | 10.1002/jrsm.1521 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Synthesis_of_evidence_from_zero_events_studies_A_comparison_of_one_stage_framework_methods/22258243 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Mathematical sciences Statistics Education |
| dc.title.none.fl_str_mv | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p></p><div> <p>In evidence synthesis, dealing with zero-events studies is an important and complicated task that has generated broad discussion. Numerous methods provide valid solutions to synthesizing data from studies with zero-events, either based on a frequentist or a Bayesian framework. Among frequentist frameworks, the one-stage methods have their unique advantages to deal with zero-events studies, especially for double-arm-zero-events. In this article, we give a concise overview of the one-stage frequentist methods. We conducted simulation studies to compare the statistical properties of these methods to the two-stage frequentist method (continuity correction) for meta-analysis with zero-events studies when double-zero-events studies were included. Our simulation studies demonstrated that the generalized estimating equation with unstructured correlation and beta-binomial method had the best performance among the one-stage methods. The random intercepts generalized linear mixed model showed good performance in the absence of obvious between-study variance. Our results also showed that the continuity correction with inverse-variance heterogeneous (IVhet) analytic model based on the two-stage framework had good performance when the between-study variance was obvious and the group size was balanced for included studies. In summary, the one-stage framework has unique advantages to deal with studies with zero events and is not susceptive to group size ratio. It should be considered in future meta-analyses whenever possible.</p> </div><p></p><h2>Other Information</h2> <p> Published in: Research Synthesis Methods<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1002/jrsm.1521" target="_blank">http://dx.doi.org/10.1002/jrsm.1521</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_b43148d99d668cfc0588dbc51c08c5cd |
| identifier_str_mv | 10.1002/jrsm.1521 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/22258243 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methodsChang Xu (102022)Luis Furuya‐Kanamori (14778820)Lifeng Lin (2034385)Mathematical sciencesStatisticsEducation<p></p><div> <p>In evidence synthesis, dealing with zero-events studies is an important and complicated task that has generated broad discussion. Numerous methods provide valid solutions to synthesizing data from studies with zero-events, either based on a frequentist or a Bayesian framework. Among frequentist frameworks, the one-stage methods have their unique advantages to deal with zero-events studies, especially for double-arm-zero-events. In this article, we give a concise overview of the one-stage frequentist methods. We conducted simulation studies to compare the statistical properties of these methods to the two-stage frequentist method (continuity correction) for meta-analysis with zero-events studies when double-zero-events studies were included. Our simulation studies demonstrated that the generalized estimating equation with unstructured correlation and beta-binomial method had the best performance among the one-stage methods. The random intercepts generalized linear mixed model showed good performance in the absence of obvious between-study variance. Our results also showed that the continuity correction with inverse-variance heterogeneous (IVhet) analytic model based on the two-stage framework had good performance when the between-study variance was obvious and the group size was balanced for included studies. In summary, the one-stage framework has unique advantages to deal with studies with zero events and is not susceptive to group size ratio. It should be considered in future meta-analyses whenever possible.</p> </div><p></p><h2>Other Information</h2> <p> Published in: Research Synthesis Methods<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1002/jrsm.1521" target="_blank">http://dx.doi.org/10.1002/jrsm.1521</a></p>2023-03-16T06:23:50ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1002/jrsm.1521https://figshare.com/articles/journal_contribution/Synthesis_of_evidence_from_zero_events_studies_A_comparison_of_one_stage_framework_methods/22258243CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/222582432023-03-16T06:23:50Z |
| spellingShingle | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods Chang Xu (102022) Mathematical sciences Statistics Education |
| status_str | publishedVersion |
| title | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| title_full | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| title_fullStr | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| title_full_unstemmed | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| title_short | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| title_sort | Synthesis of evidence from zero‐events studies: A comparison of one‐stage framework methods |
| topic | Mathematical sciences Statistics Education |