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dc.contributor.authorRodríguez Barranco, Migueles_ES
dc.contributor.authorTobías, Aurelioes_ES
dc.contributor.authorRedondon, Danieles_ES
dc.contributor.authorMolina Portillo, Elena es_ES
dc.contributor.authorSánchez Pérez, María José es_ES
dc.date.accessioned2018-03-06T09:56:52Z
dc.date.available2018-03-06T09:56:52Z
dc.date.issued2017
dc.identifier.citationRodríguez Barranco, M.; et al. Standardizing effect size from linear regression models with log-transformed variables for meta-analysis. BMC Medical Research Methodology, 17: 44 (2017). [http://hdl.handle.net/10481/49843]es_ES
dc.identifier.issn1471-2288
dc.identifier.urihttp://hdl.handle.net/10481/49843
dc.description.abstractBackground: Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. Methods: We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. Results: In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. Conclusions: The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables.en_EN
dc.language.isoenges_ES
dc.publisherBiomed Centralen_EN
dc.subjectMeta-analysisen_EN
dc.subjectSystematic reviewen_EN
dc.subjectLog-transformationen_EN
dc.subjectLinear regressionen_EN
dc.subjectEffect sizeen_EN
dc.subjectRegression coefficientsen_EN
dc.titleStandardizing effect size from linear regression models with log-transformed variables for meta-analysisen_EN
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1186/s12874-017-0322-8


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