Rol' leptina v razvitii bronkhial'noy astmy u detey.

Güler, Nurcan; Kirerleri, E; Öneş, Ülker; Tamay, Zeynep; Salmayenli, Nihal

doi:10.14341/2071-8713-4934

Cited by 1 publication

(2 citation statements)

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“…(2011), Kim et al (2008) and Guler et al (2004)) is not suitable to further conduct the sample mean and standard deviation estimation. We suggest to exclude these five studies from the meta-analysis of investigating the association between leptin serum level and asthma.…”

Section: Results Of Symmetry Test and Meta-analysismentioning

confidence: 99%

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Testing normality using the summary statistics with application to meta-analysis

Luo,

Wan,

Liu

et al. 2018

Preprint

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As the most important tool to provide high-level evidence-based medicine, researchers can statistically summarize and combine data from multiple studies by conducting meta-analysis. In meta-analysis, mean differences are frequently used effect size measurements to deal with continuous data, such as the Cohen's d statistic (Cohen, 2013) and Hedges' g statistic (Hedges, 1981) values. To calculate the mean difference based effect sizes, the sample mean and standard deviation are two essential summary measures. However, many of the clinical reports tend not to directly record the sample mean and standard deviation. Instead, the sample size, median, minimum and maximum values and/or the first and third quartiles are reported. As a result, researchers have to transform the reported information to the sample mean and standard deviation for further compute the effect size. Since most of the popular transformation methods were developed upon the normality assumption of the underlying data, it is necessary to perform a pre-test before transforming the summary statistics. In this article, we had introduced test statistics for three popular scenarios in meta-analysis. We suggests medical researchers to perform a normality test of the selected studies before using them to conduct further analysis. Moreover, we applied three different case studies to demonstrate the usage of the newly proposed test statistics. The real data case studies indicate that the new test statistics are easy to apply in practice and by following the recommended path to conduct the meta-analysis, researchers can obtain more reliable conclusions.

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Section: Results Of Symmetry Test and Meta-analysismentioning

confidence: 99%

“…tremum, test statistic T 2 is applied to studies da Silva et al (2012),Giouleka et al (2011), Leivo-Korpela et al (2011,Kim et al (2008) andGuler et al (2004). To further proceed meta-analysis, it is more reliable to only transform the studies with symmetric data, to the sample mean and standard deviation via methods proposed byLuo et al (2017) andWan et al (…”

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confidence: 99%