Bias in meta‐analyses using Hedges’ <i>d</i>

Hamman, Elizabeth; Pappalardo, Paula; Bence, James R.; Peacor, Scott D.; Osenberg, Craig W.

doi:10.1002/ecs2.2419

Cited by 44 publications

(55 citation statements)

References 37 publications

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“…We considered this example in Section 7. In ecology, typical sample sizes are between 4 and 25 . An effect‐measure‐specific estimator of τ 2 , such as KDB for SMD, can reduce inherent biases.…”

Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

“…A pragmatic approach to unbiased estimation of δ uses weights that do not involve estimated variances of study‐level estimates, for example, weights proportional to the study sizes n i . Hunter and Schmidt and Shuster, among others, have proposed such weights, and Marín‐Martínez and Sánchez‐Meca and Hamman et al have studied the method's performance by simulation for SMD. We prefer to use weights proportional to an effective sample size,

{\overset{n}{true}}_{i} = n_{i T} n_{i C} false/ n_{i}

; these are the optimal inverse‐variance weights for SMD when δ =0 and τ 2 =0.…”

Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

“…Thus, the overall effect is estimated by

{\overset{θ}{true}}_{S S W} = \sum {\overset{n}{true}}_{i} {\overset{θ}{true}}_{i} false/ \sum {\overset{n}{true}}_{i}

, and its variance is estimated by Equation . Hamman et al use weights proposed by Hedges, which differ slightly from

\overset{n}{true}

for very small sample sizes. A good estimator of τ 2 , such as MP or KDB (for SMD), can be used as

{\overset{τ}{true}}^{2}

.…”

Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

See 2 more Smart Citations

Estimation in meta‐analyses of mean difference and standardized mean difference

Bakbergenuly

Hoaglin

Kulinskaya

2019

Statistics in Medicine

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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 approximations to the expected value of Q for both MD and SMD to introduce two new methods of point estimation of τ 2 for MD (Welch‐type and corrected DerSimonian‐Laird) and one WT interval method. We also introduce one point estimator and one interval estimator for τ 2 in SMD. Extensive simulations compare our methods with four point estimators of τ 2 (the popular methods of DerSimonian‐Laird, restricted maximum likelihood, and Mandel and Paule, and the less‐familiar method of Jackson) and four interval estimators for τ 2 (profile likelihood, Q‐profile, Biggerstaff and Jackson, and Jackson). We also study related point and interval estimators of the overall effect, including an estimator whose weights use only study‐level sample sizes. We provide measure‐specific recommendations from our comprehensive simulation study and discuss an example.

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Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

{\overset{n}{true}}_{i} = n_{i T} n_{i C} false/ n_{i}

; these are the optimal inverse‐variance weights for SMD when δ =0 and τ 2 =0.…”

Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

“…Thus, the overall effect is estimated by

{\overset{θ}{true}}_{S S W} = \sum {\overset{n}{true}}_{i} {\overset{θ}{true}}_{i} false/ \sum {\overset{n}{true}}_{i}

, and its variance is estimated by Equation . Hamman et al use weights proposed by Hedges, which differ slightly from

\overset{n}{true}

for very small sample sizes. A good estimator of τ 2 , such as MP or KDB (for SMD), can be used as

{\overset{τ}{true}}^{2}

.…”

Section: Discussion: Practical Implications For Meta‐analysismentioning

confidence: 99%

See 1 more Smart Citation

Estimation in meta‐analyses of mean difference and standardized mean difference

Bakbergenuly

Hoaglin

Kulinskaya

2019

Statistics in Medicine

View full text Add to dashboard Cite

show abstract

“…Where such outliers existed, we reran the analyses without them to assess their influence on our results. Although a common approach in meta‐analyses, weighting by inverse variance has recently been argued to result in biased results in some instances (Hamman, Pappalardo, Bence, Peacor, & Osenberg, ). We therefore also ran all analyses weighting by sample size, but found no difference in our results.…”

Section: Methodsmentioning

confidence: 99%

“…Although a common approach in meta-analyses, weighting by inverse variance has recently been argued to result in biased results in some instances (Hamman, Pappalardo, Bence, Peacor, & Osenberg, 2018).…”

Section: Publication Bias/sensitivity Analysismentioning

confidence: 99%

Fitness consequences of different migratory strategies in partially migratory populations: A multi‐taxa meta‐analysis

Buchan

Gilroy

Catry

et al. 2019

Journal of Animal Ecology

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Partial migration—wherein migratory and non‐migratory individuals exist within the same population—represents a behavioural dimorphism; for it to persist over time, both strategies should yield equal individual fitness. This balance may be maintained through trade‐offs where migrants gain survival benefits by avoiding unfavourable conditions, while residents gain breeding benefits from early access to resources. There has been little overarching quantitative analysis of the evidence for this fitness balance. As migrants—especially long‐distance migrants—may be particularly vulnerable to environmental change, it is possible that recent anthropogenic impacts could drive shifts in fitness balances within these populations. We tested these predictions using a multi‐taxa meta‐analysis. Of 2,939 reviewed studies, 23 contained suitable information for meta‐analysis, yielding 129 effect sizes. Of these, 73% (n = 94) reported higher resident fitness, 22% (n = 28) reported higher migrant fitness, and 5% (n = 7) reported equal fitness. Once weighted for precision, we found balanced fitness benefits across the entire dataset, but a consistently higher fitness of residents over migrants in birds and herpetofauna (the best‐sampled groups). Residency benefits were generally associated with survival, not breeding success, and increased with the number of years of data over which effect sizes were calculated, suggesting deviations from fitness parity are not due to sampling artefacts. A pervasive survival benefit to residency documented in recent literature could indicate that increased exposure to threats associated with anthropogenic change faced by migrating individuals may be shifting the relative fitness balance between strategies.

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Evaluating impacts of non‐native submerged aquatic vegetation on native nekton

Wellman,

Trackenberg,

Gilliland

et al. 2023

Ecosphere

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The introduction and spread of non‐native species restructure native ecosystems and can be particularly impactful when invaders are ecosystem engineers or habitat‐forming species. In coastal, estuarine, and marine systems, submerged aquatic vegetation (SAV), like macroalgae and seagrasses, form key habitats for nekton, serving as nurseries, foraging grounds, and reproduction sites. If non‐native ecosystem engineers can provide sufficient structure and/or resources, they may exert a neutral or positive effect on organisms occupying higher trophic positions. As such, we hypothesized that nekton response to non‐native SAV species may be neutral or positive. We performed a quantitative meta‐analysis to quantify impacts of non‐native SAV on native crabs, fishes, and shrimps. We extracted data from 35 studies and evaluated 11 response metrics related to facilitation (e.g., habitat use and foraging), restricting our analysis to studies that compared at least one of these metrics in nekton from co‐occurring native and non‐native SAV habitats in marine, coastal, or estuarine systems. We found that nekton abundance, species richness, and biomass were the most assessed metrics of nekton performance. Our pooled data revealed differential results among response metrics, with nekton growth and reproduction enhanced in non‐native habitats and species richness enhanced in a native setting. The mean effect sizes for all other nekton response metrics, including abundance, had 95% CIs that overlapped zero, indicating no difference in response between native and non‐native SAV. For many endpoints, limited sample sizes prevented robust inferences, but they also highlighted areas where more research is needed in future studies. Non‐native species have the potential to restructure the systems they invade. Our results lend support to the relative trophic position hypothesis, indicating that non‐native habitat formers may facilitate native organisms in higher trophic levels. We identify research gaps that may guide future studies and allow for a more comprehensive understanding of responses to non‐native ecosystem engineers.

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Bias in meta‐analyses using Hedges’ d

Cited by 44 publications

References 37 publications

Estimation in meta‐analyses of mean difference and standardized mean difference

Estimation in meta‐analyses of mean difference and standardized mean difference

Fitness consequences of different migratory strategies in partially migratory populations: A multi‐taxa meta‐analysis

Evaluating impacts of non‐native submerged aquatic vegetation on native nekton

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