2013
DOI: 10.1002/pst.1601
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A comparison of statistical methods for combining relative bioactivities from parallel line bioassays

Abstract: This paper compares the ordinary unweighted average, weighted average, and maximum likelihood methods for estimating a common bioactivity from multiple parallel line bioassays. Some of these or similar methods are also used in meta-analysis. Based on a simulation study, these methods are assessed by comparing coverage probabilities of the true relative bioactivity and the length of the confidence intervals computed for these methods. The ordinary unweighted average method outperforms all statistical methods by… Show more

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Cited by 5 publications
(4 citation statements)
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“…For meta‐analyses with a very small number of studies, our approach can still be improved by implementing the appropriate degrees of freedom when the between‐study variance is estimated zero. This would also be true for the other conservative methods (Mzolo et al., 2013 ).…”
Section: Resultsmentioning
confidence: 87%
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“…For meta‐analyses with a very small number of studies, our approach can still be improved by implementing the appropriate degrees of freedom when the between‐study variance is estimated zero. This would also be true for the other conservative methods (Mzolo et al., 2013 ).…”
Section: Resultsmentioning
confidence: 87%
“…The conservative coverage probabilities are explained by the incorrect use of the degrees of freedom in the t ‐quantile. The estimates for the between‐study variance frequently vanishes, which would imply that the degrees of freedom for the estimated standard error of the pooled effect size is much closer to the sum of all the degrees of freedom in the meta‐analysis study (Cochran, 1954 ; Mzolo et al., 2013 ). In that case, a normal quantile is warranted or one could update the degrees of freedom in the t ‐quantile.…”
Section: Resultsmentioning
confidence: 99%
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“…Note that it has been more common in literature to use the normal quantile instead of the quantile of the t-distribution (Brockwell and Gordon, 2007;Thorlund et al, 2011;Jackson et al, 2010), but we believe that DerSimonian and Laird were not explicit on this topic (DerSimonian and Laird, 1986) and therefore did not rule out our preferred choice. We believe that our choice is in line with the work of Cochran (Cochran, 1954), who proposed to use the t-distribution with m − 1 degrees of freedom instead of the normal distribution, in particular in the presence of heterogeneity (see also Mzolo et al (2013)). The use of this t-distribution is common when the corrected standard error of Hartung-Knapp-Sidik-Jonkman is used (Sidik and Jonkman, 2005) .…”
Section: The Dersimonian-laird Methodsmentioning
confidence: 78%