Spanish
modelo de efectos fijos 1
A random effects model was used to process the data for analysis.
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Therefore, to account for residual heterogeneity, a random effects model was estimated.
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Fixed or random effects models were adopted to estimate overall relative risk.
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Group differences in mental health outcomes were assessed using random effects meta-analyses.
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Meta-analysis of perioperative outcome measures was carried out using a random effects model.
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Pooled estimates of overall treatment effect were calculated using a random effects model.
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Results: We identified six papers with sufficient data for a random effects meta-analysis.
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Where data allowed, we performed meta-analysis and pooled results using random effects models.
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The results were analysed using the intention-to-treat principle and linear random effects modelling.
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Subsequently, random effects meta-analysis was used to pool the interaction terms.
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The additive genetic, permanent environmental and residual effects were included as random effects.
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We then produced pooled estimates across studies using random effects meta-analyses.
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Bias is reduced by including sufficient between-study random effects in the imputation model.
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Summary relative risks were estimated by the use of a random effects model.
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These models often assume that the random effects are normally distributed.
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Median values were obtained for each estimate using random effects meta-analysis.
