Please use this identifier to cite or link to this item:
https://olympias.lib.uoi.gr/jspui/handle/123456789/29117Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Πετροπούλου, Μαρία | el |
| dc.contributor.author | Μαυρίδης, Δημήτρης | el |
| dc.date.accessioned | 2018-05-22T10:50:15Z | - |
| dc.date.available | 2018-05-22T10:50:15Z | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/29117 | - |
| dc.rights | An error occurred on the license name. | * |
| dc.rights.uri | An error occurred getting the license - uri. | * |
| dc.subject | bias | en |
| dc.subject | type I error | en |
| dc.subject | heterogeneity variance estimators | en |
| dc.subject | power | en |
| dc.subject | simulation study | en |
| dc.title | A comparison of 20 heterogeneity variance estimators in statistical synthesis of results from studies | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο περιοδικού | el |
| heal.secondaryTitle | A simulation study | en |
| heal.dateAvailable | 2018-05-22T10:51:15Z | - |
| heal.language | en | - |
| heal.access | free | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Αγωγής. Παιδαγωγικό Τμήμα Δημοτικής Εκπαίδευσης. | el |
| heal.publicationDate | 2017 | - |
| heal.bibliographicCitation | - | en |
| heal.abstract | When we synthesize research findings via meta-analysis, it is common to assume that the true underlying effect differs across studies. There is a plethora of estimation methods available for the between-study variability. The widely used DerSimonian and Laird estimation method has been challenged but knowledge for the overall performance of heterogeneity estimators is incomplete. We identified 20 heterogeneity estimators in the literature and evaluated their performance in terms of bias, type error I rate and power via a simulation study. Moreover, we compared the Knapp and Hartung and the Wald-type method for estimating confidence interval for the summary estimate. Although previous simulation studies have suggested the Paule-Mandel (PM) estimator, it has not been compared with all the available estimators. For dichotomous outcomes, estimating heterogeneity through Markov Chain Monte Carlo is a good choice if the prior distribution for heterogeneity is informed by published Cochrane reviews. Non parametric bootstrap (DLb) performs well for all assessment criteria for both dichotomous and continuous outcomes. The positive DerSimonian and Laird (DLp) and the Hartung-Makambi (HM) estimators can be an alternative choice for dichotomous outcome when the heterogeneity values are close to 𝟎.𝟎𝟕 and for continuous outcome for all and for medium heterogeneity values (𝟎.𝟎𝟏,𝟎.𝟎𝟓), respectively. Hence, they are heterogeneity estimators (DLb; DLp) which perform better than the suggested PM. Maximum likelihood (ML) provide the best performance for both types of outcome in the absence of heterogeneity. | en |
| heal.publisher | Wiley | en |
| heal.journalName | Statistics in Medicine | en |
| heal.journalType | peer-reviewed | - |
| heal.fullTextAvailability | true | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Heterogeneity- Simulation study.pdf | Κύριο Άρθρο | 643.07 kB | Adobe PDF | View/Open |
| figures_supplementary.pdf | Συμπληρωματικοί πίνακες | 592.63 kB | Adobe PDF | View/Open |
| sup-0001-supplementary.pdf | Συμπληρωματικά στοιχεία | 316.47 kB | Adobe PDF | View/Open |
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