Meta‐analysis of quantile intervals from different studies with an application to a pulmonary tuberculosis data

Öztürk, Ömer

doi:10.1002/sim.8738

Cited by 7 publications

(26 citation statements)

References 23 publications

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“…In this context, our meta-analytical study has completed the first step in this research journey that should be complemented by future meta-analytical work of quantile intervals as the research field matures (Ozturk & Balakrishnan, 2020), explicitly accounting for the non-normal distribution of the EP of FFs.…”

Section: Discussionmentioning

confidence: 99%

Family Firms and Environmental Performance: A Meta-Analytic Review

Miroshnychenko

Massis

Barontini

et al. 2022

Family Business Review

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This article critically reviews and meta-analyzes the environmental performance of family firms. Using a sample of 40,910 firms covering a 12-year period, we conclude that the average effect of family involvement on environmental performance is negative, albeit small. This negative effect is more pronounced in primary studies that measure environmental performance via the environmental operational practices adopted and in those that define family business using the family ownership and management criteria. Our findings suggest that from an agency perspective, and compared with nonfamily firms, the negative view of the environmental performance of family firms prevails over the positive view.

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Section: Discussionmentioning

confidence: 99%

Family Firms and Environmental Performance: A Meta-Analytic Review

Miroshnychenko

Massis

Barontini

et al. 2022

Family Business Review

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“…As the variance of the outcome distribution is often incredibly large in such cases, these primary studies receive a weight of nearly 0 in the meta-analysis and cause numerical problems when estimating the between-study variance. As previously considered in the context of meta-analysis of studies reporting medians [7,22,23,24], we used Bowley's coefficient [27] to quantify skewness based on the S 2 summary statistics. We removed primary studies when Bowley's coefficient was greater than 0.75.…”

Section: Additional Description and Results For The Data Application ...mentioning

confidence: 99%

“…However, it should be noted that a number of other approaches have been proposed in more case-specific contexts. One line of approaches estimates a pooled median or the difference of medians across two groups [22,23,24]. Another approach estimates a global location parameter or the difference in global location parameters under a suitable location-scale model [12].…”

Section: Discussionmentioning

confidence: 99%

Standard error estimation in meta-analysis of studies reporting medians

McGrath¹,

Katzenschlager²,

Zimmer³

et al. 2022

Preprint

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We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this paper, we illustrate how this common practice can severely underestimate the withinstudy standard errors, which results in overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve estimation of the within-study standard errors and between-study heterogeneity. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.

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“…One line of approaches estimates a pooled median or the difference of medians across two groups. 24–26 Another approach estimates a global location parameter or the difference in global location parameters under a suitable location-scale model. 13…”

Section: Discussionmentioning

confidence: 99%

“…One line of approaches estimates a pooled median or the difference of medians across two groups. [24][25][26] Another approach estimates a global location parameter or the difference in global location parameters under a suitable location-scale model. 13 It should also be noted that primary studies sometimes report summary measures of the outcome on the logarithmic scale when the distribution of outcome is skewed.…”

Section: Discussionmentioning

confidence: 99%

Standard error estimation in meta-analysis of studies reporting medians

McGrath

Katzenschlager

Zimmer

et al. 2022

Stat Methods Med Res

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We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some primary studies report the sample mean and standard deviation of the outcome and other studies report the sample median along with the first and third quartiles and/or minimum and maximum values. To perform meta-analysis in this context, a number of approaches have recently been developed to impute the sample mean and standard deviation from studies reporting medians. Then, standard meta-analytic approaches with inverse-variance weighting are applied based on the (imputed) study-specific sample means and standard deviations. In this article, we illustrate how this common practice can severely underestimate the within-study standard errors, which results in poor coverage for the pooled mean in common effect meta-analyses and overestimation of between-study heterogeneity in random effects meta-analyses. We propose a straightforward bootstrap approach to estimate the standard errors of the imputed sample means. Our simulation study illustrates how the proposed approach can improve the estimation of the within-study standard errors and consequently improve coverage for the pooled mean in common effect meta-analyses and estimation of between-study heterogeneity in random effects meta-analyses. Moreover, we apply the proposed approach in a meta-analysis to identify risk factors of a severe course of COVID-19.

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Meta‐analysis of quantile intervals from different studies with an application to a pulmonary tuberculosis data

Cited by 7 publications

References 23 publications

Family Firms and Environmental Performance: A Meta-Analytic Review

Family Firms and Environmental Performance: A Meta-Analytic Review

Standard error estimation in meta-analysis of studies reporting medians

Standard error estimation in meta-analysis of studies reporting medians

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