| dc.creator | Zintzaras, E. | en |
| dc.creator | Ioannidis, J. P. | en |
| dc.date.accessioned | 2015-11-23T10:55:10Z | |
| dc.date.available | 2015-11-23T10:55:10Z | |
| dc.date.issued | 2014 | |
| dc.identifier | 10.1016/j.cmpb.2014.06.009 | |
| dc.identifier.issn | 0169-2607 | |
| dc.identifier.uri | http://hdl.handle.net/11615/34948 | |
| dc.description.abstract | Meta-analysis aims to synthesize results from different studies. Although, in a meta-analysis the presence of large between-study heterogeneity is routinely evaluated, in some instances is also important to probe whether there is extreme between-study homogeneity (i.e. extreme low between-study heterogeneity). HELOW (HEterogeneity LOW) is a program for testing extreme homogeneity in a meta-analysis of risk ratios when binary outcome and Mantel-Haenszel fixed effects summary risk ratio estimate are employed. The significance of extreme homogeneity is assessed using a Monte Carlo test. Extreme homogeneity may yield insights for the statistical and clinical interpretation of the data. (C) 2014 Elsevier Ireland Ltd. All rights reserved. | en |
| dc.source | Computer Methods and Programs in Biomedicine | en |
| dc.source.uri | <Go to ISI>://WOS:000343091400031 | |
| dc.subject | Meta-analysis | en |
| dc.subject | Homogeneity | en |
| dc.subject | Heterogeneity | en |
| dc.subject | Monte Carlo | en |
| dc.subject | Risk ratio | en |
| dc.subject | 2 X-2 TABLES | en |
| dc.subject | HETEROGENEITY | en |
| dc.subject | RATIO | en |
| dc.subject | Computer Science, Interdisciplinary Applications | en |
| dc.subject | Computer Science, | en |
| dc.subject | Theory & Methods | en |
| dc.subject | Engineering, Biomedical | en |
| dc.subject | Medical Informatics | en |
| dc.title | HELOW: A program for testing extreme homogeneity in meta-analysis | en |
| dc.type | journalArticle | en |