Comparison of four heterogeneity measures for meta‐analysis

Lin, Lifeng

doi:10.1111/jep.13159

Cited by 84 publications

(61 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The statistical significance was determined by Z test, and P -value < 0.05 was considered as statistically significant. Heterogeneity was tested using the Cochran’s Q test and measured inconsistency by I 2 [35]. Data with low heterogeneity ( P > 0.10 and I 2 < 50%) were analyzed by a fixed-effects model while a random-effect model was used for data with high heterogeneity ( P ≤ 0.10 and I 2 ≥ 50%).…”

Section: Methodsmentioning

confidence: 99%

Associations betweenCYP3A4, CYP3A5andSCN1APolymorphisms and Carbamazepine Metabolism in Epilepsy: A Meta-analysis

Zhao

Zhang

Cai³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background and objective: CYP3A4 (rs2242480), CYP3A5 (rs776746) and SCN1A (rs3812718 and rs2298771) gene polymorphisms were previously indicated to be associated with carbamazepine (CBZ) metabolism and resistance in epilepsy. However, previous studies regarding the effects of these polymorphisms still remain controversial. Therefore, we performed a meta-analysis to evaluate whether the four polymorphisms are associated with CBZ metabolism and resistance. Methods: The PubMed, EMBASE, Cochrane library, Chinese National Knowledge Infrastructure, Chinese Science and Technique Journals Database, China Biology Medicine disc and Wan fang Database were searched up to January 2020 for appropriate studies regarding the association of rs2242480, rs776746, rs3812718 and rs2234922 polymorphisms with metabolism and resistance to CBZ. The meta-analysis was conducted by Review Manager 5.3 software. Results: Eighteen studies involving 2574 related epilepsy patients were included. Significant associations between CYP3A4 rs2242480, CYP3A5 rs776746 and SCN1A rs3812718 polymorphisms and plasma concentrations of CBZ were observed. Additionally, SCN1A rs3812718 polymorphism was significantly associated with CBZ resistance. However, no association was observed between SCN1A rs2298771 polymorphism and metabolism and resistance to CBZ. Conclusion: The CYP3A4 rs2242480, CYP3A5 rs776746 and SCN1A rs3812718 polymorphisms may play important roles in metabolism and resistance to CBZ, while SCN1A rs2298771 polymorphism is not associated with CBZ in epilepsy. These findings would improve the individualized therapy of epileptic patients in clinics.

show abstract

Section: Methodsmentioning

confidence: 99%

Associations betweenCYP3A4, CYP3A5andSCN1APolymorphisms and Carbamazepine Metabolism in Epilepsy: A Meta-analysis

Zhao

Zhang

Cai³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Note that the constant counterpart, I 2 , would instead have τ 2 in Equation ( 16). This raises the question of choosing a value for s 2 , with recent proposals including the harmonic or arithmetic mean (Table 1, Lin, 2020). The most common estimator is that of Higgins and Thompson (2002), which was "originally motivated by the expectation of the Q statistic" (p, 378 Lin, 2020).…”

Section: Heterogeneity Statisticsmentioning

confidence: 99%

Putting Variation into Variance: Modeling Between-Study Heterogeneity in Meta-Analysis

Dr¹,

Rodriguez²,

Bürkner³

2021

Preprint

View full text Add to dashboard Cite

We shed much needed light upon a critical assumption that is oft-overlooked---or not considered at all---in random-effects meta-analysis.Namely, that between-study variance is constant across \emph{all} studies which implies they are from the \emph{same} population. Yet it is not hard to imagine a situation where there are several and not merely one population of studies, perhaps differing in their between-study variance (i.e., heteroskedasticity). The objective is to then make inference, given that there are variations in heterogeneity. There is an immediate problem, however, in that modeling heterogeneous variance components is not straightforward to do in a general way. To this end, we propose novel methodology, termed Bayesian location-scale meta-analysis, that can accommodate moderators for both the overall effect (location) and the between-study variance (scale). After introducing the model, we then extend heterogeneity statistics, prediction intervals, and hierarchical shrinkage, all of which customarily assume constant heterogeneity, to include variations therein. With these new tools in hand, we go to work demonstrating that quite literally \emph{everything} changes when between-study variance is not constant across studies. The changes were not small and easily passed the interocular trauma test---the importance hits right between the eyes. Such examples include (but are not limited to) inference on the overall effect, a compromised predictive distribution, and improper shrinkage of the study-specific effects. Further, we provide an illustrative example where heterogeneity was not considered a mere nuisance to show that modeling variance for its own sake can provide unique inferences, in this case into discrimination across nine countries. The discussion includes several ideas for future research. We have implemented the proposed methodology in the {\tt R} package \textbf{blsmeta}.

show abstract

“…The I 2 test of heterogeneity will be used to determine the level of variation related to diversity rather than chance. Rather than simply stating whether heterogeneity is present or not, it will be measured using I 2 test [24]. Low heterogeneity will be re ected as an I 2 result between 0-40%; moderate heterogeneity between 30-60%; substantial heterogeneity between 50-90%; and considerable heterogeneity between 75-100% [25].…”

Section: Data Synthesismentioning

confidence: 99%

The Impact of Design Elements on Undergraduate Nursing Students’ Educational Outcomes in Simulation Education: Protocol for a Systematic Review

Jackson

McTier

Brooks

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Although simulation-based education (SBE) has become increasingly popular as a mode of teaching in undergraduate nursing courses its effect on associated student learning outcomes remains ambiguous. Educational outcomes are influenced by SBE quality that is governed by technology, training, resources and SBE design elements. This paper reports the protocol for a systematic review to identify, appraise and synthesise the best available evidence regarding the impact of SBE on undergraduate nurses’ learning outcomes. Methods: Databases to be searched from 1st of January 1990 include the Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Medical Literature Analysis and Retrieval System Online (MEDLINE), American Psychological Association (APA) PsycInfo and the Education Resources Information Centre (ERIC) via the EBSCO host platform. The Excerpta Medica database (EMBASE) will be searched via the OVID platform. We will review the reference lists of relevant articles for additional citations. A combination of search terms including ‘nursing students’, ‘simulation training, ‘patient simulation’, and ‘immersive simulation’ with common Boolean operators will be used. Specific search terms will be combined with either MeSH or Emtree terms and appropriate permutations for each database. Search findings will be imported into reference management software (Endnote© Version.X9) then uploaded into Covidence where two reviewers will independently screen titles, abstracts and retrieved full text. A third reviewer will be available to resolve conflicts and moderate consensus discussions. Quantitative primary research studies evaluating the effect of SBE on undergraduate nursing students’ educational outcomes will be included. The Mixed Methods Appraisal Tool (MMAT) will be used for quality assessment of core criteria, in addition to the Cochrane RoB 2 and ROBINS-I to assess risk of bias for randomised and non-randomised studies, respectively. Primary outcomes are any measure of knowledge, skills, or attitude. Discussion: SBE has been widely adopted by healthcare disciplines in tertiary teaching settings. This systematic review will reveal (i) the effect of SBE on learning outcomes, (ii) SBE element variability, and (iii) interplay between SBE elements and learning outcome. Findings will specify SBE design elements to inform the design and implementation of future strategies for simulation-based undergraduate nursing education.Systematic Review Registration: PROSPERO CRD42021244530

show abstract

Comparison of four heterogeneity measures for meta‐analysis

Cited by 84 publications

References 47 publications

Associations betweenCYP3A4, CYP3A5andSCN1APolymorphisms and Carbamazepine Metabolism in Epilepsy: A Meta-analysis

Associations betweenCYP3A4, CYP3A5andSCN1APolymorphisms and Carbamazepine Metabolism in Epilepsy: A Meta-analysis

Putting Variation into Variance: Modeling Between-Study Heterogeneity in Meta-Analysis

The Impact of Design Elements on Undergraduate Nursing Students’ Educational Outcomes in Simulation Education: Protocol for a Systematic Review

Contact Info

Product

Resources

About