2019
DOI: 10.1002/sim.8422
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Estimation in meta‐analyses of mean difference and standardized mean difference

Abstract: Methods for random‐effects meta‐analysis require an estimate of the between‐study variance, τ 2. The performance of estimators of τ 2 (measured by bias and coverage) affects their usefulness in assessing heterogeneity of study‐level effects and also the performance of related estimators of the overall effect. However, as we show, the performance of the methods varies widely among effect measures. For the effect measures mean difference (MD) and standardized MD (SMD), we use improved effect‐measure‐specific app… Show more

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Cited by 42 publications
(57 citation statements)
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“…55 For meta-analyses of SMDs, measure-specific variance estimators are available. 75 In future studies, it is worthwhile to investigate their performance for the different point and variance estimators of the SMD reviewed in this article.…”
Section: Discussionmentioning
confidence: 99%
“…55 For meta-analyses of SMDs, measure-specific variance estimators are available. 75 In future studies, it is worthwhile to investigate their performance for the different point and variance estimators of the SMD reviewed in this article.…”
Section: Discussionmentioning
confidence: 99%
“…After matching, to assess the balance between the two groups, the standardized mean differences (SMDs) between the TTE cohort and the non-TTE cohort were calculated. SMDs eliminate not only the in uence of the absolute values from a study but also the in uence of the unit of measurement on the results [19]. Continuous variables are shown as the means and standard deviation, and categorical variables are represented as the total and proportion.…”
Section: Methodsmentioning
confidence: 99%
“…When analyzing the difference of continuous data, the mean difference (MD) with 95% con dence interval (CI) is used as the effect size [23]; when analyzing the difference of the binary data, the relative risk (RR) with 95% CI is used as the effect size. Heterogeneity was examined using the I 2 statistic that indicates the proportion of total variability in estimates that can be attributed to heterogeneity [24].…”
Section: Introductionmentioning
confidence: 99%