Comparing the Sample-Weighted and Unweighted Meta-Analysis: An Applied Perspective

1999 ◽  
Vol 25 (6) ◽  
pp. 803-828 ◽  
Author(s):  
J. Bryan Fuller ◽  
Kim Hester
Keyword(s):  
Confidence Intervals ◽  
Meta Analysis ◽  
Error Variance ◽  
Actual Data ◽  
Sampling Variance ◽  
Average Correlation ◽  
Simulation Research ◽  
Actual Application ◽  
Sample Error ◽  
Variance Estimates

An extensive comparison of the sample-weighted method (Hunter & Schmidt, 1990), and a newer unweighted method (Osburn & Callender, 1992) of meta-analysis is presented using actual data. Several of the advantages of the unweighted method predicted by Osburn and Callendar’s simulation research did not always hold in actual application. Specifically, the unweighted method did not always produce larger estimates of observed variance, credibility intervals, and confidence intervals than the sample-weighted method when large sample outliers are present. Also, Osburn and Callender’s research on mean sampling variance formulae did not generalize to meta-analysis using the average correlation estimator to measure sample error variance. Finally, results show that while both methods may generate similar parameter and variance estimates in primary meta-analysis, they may lead researchers to reach different substantive conclusions in the analysis of moderators.

A Meta-Analysis of the Facial Feedback Literature: Effects of Facial Feedback on Emotional Experience Are Small and Variable

2017 ◽  
Author(s):  
Nicholas Alvaro Coles ◽  
Jeff T. Larsen ◽  
Heather Lench
Keyword(s):  
Publication Bias ◽  
Emotional Experience ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Detection Methods ◽  
Feedback Effects ◽  
Facial Feedback ◽  
Facial Movements ◽  
Facial Feedback Hypothesis ◽  
Variance Estimates

The facial feedback hypothesis suggests that an individual’s experience of emotion is influenced by feedback from their facial movements. To evaluate the cumulative evidence for this hypothesis, we conducted a meta-analysis on 286 effect sizes derived from 138 studies that manipulated facial feedback and collected emotion self-reports. Using random effects meta-regression with robust variance estimates, we found that the overall effect of facial feedback was significant, but small. Results also indicated that feedback effects are stronger in some circumstances than others. We examined 12 potential moderators, and three were associated with differences in effect sizes. 1. Type of emotional outcome: Facial feedback influenced emotional experience (e.g., reported amusement) and, to a greater degree, affective judgments of a stimulus (e.g., the objective funniness of a cartoon). Three publication bias detection methods did not reveal evidence of publication bias in studies examining the effects of facial feedback on emotional experience, but all three methods revealed evidence of publication bias in studies examining affective judgments. 2. Presence of emotional stimuli: Facial feedback effects on emotional experience were larger in the absence of emotionally evocative stimuli (e.g., cartoons). 3. Type of stimuli: When participants were presented with emotionally evocative stimuli, facial feedback effects were larger in the presence of some types of stimuli (e.g., emotional sentences) than others (e.g., pictures). The available evidence supports the facial feedback hypothesis’ central claim that facial feedback influences emotional experience, although these effects tend to be small and heterogeneous.

scholarly journals Association of bisphenol A with puberty timing: a meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Hui Meng ◽  
Yunping Zhou ◽  
Yunxia Jiang
Keyword(s):  
Bisphenol A ◽  
Confidence Intervals ◽  
Random Effects ◽  
Strong Correlation ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Random Effects Models ◽  
Study Heterogeneity ◽  
The Relationship ◽  
Prevalence Ratios

AbstractObjectivesThe results of existing studies on bisphenol A (BPA) and puberty timing did not reach a consensus. Thereby we performed this meta-analytic study to explore the association between BPA exposure in urine and puberty timing.MethodsMeta-analysis of the pooled odds ratios (OR), prevalence ratios (PR) or hazards ratios (HR) with 95% confidence intervals (CI) were calculated and estimated using fixed-effects or random-effects models based on between-study heterogeneity.ResultsA total of 10 studies involving 5621 subjects were finally included. The meta-analysis showed that BPA exposure was weakly associated with thelarche (PR: 0.96, 95% CI: 0.93–0.99), while no association was found between BPA exposure and menarche (HR: 0.99, 95% CI: 0.89–1.12; OR: 1.02, 95% CI: 0.73–1.43), and pubarche (OR: 1.00, 95% CI: 0.79–1.26; PR: 1.00, 95% CI: 0.95–1.05).ConclusionsThere was no strong correlation between BPA exposure and puberty timing. Further studies with large sample sizes are needed to verify the relationship between BPA and puberty timing.

scholarly journals Evaluation of Inter-Observer Reliability of Animal Welfare Indicators: Which Is the Best Index to Use?

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1445
Author(s):  
Mauro Giammarino ◽  
Silvana Mattiello ◽  
Monica Battini ◽  
Piero Quatto ◽  
Luca Maria Battaglini ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Confidence Intervals ◽  
Bootstrap Method ◽  
Dairy Goat ◽  
Microsoft Excel ◽  
Bootstrap Methods ◽  
Welfare Indicators ◽  
Observer Reliability ◽  
High Concordance ◽  
Variance Estimates

This study focuses on the problem of assessing inter-observer reliability (IOR) in the case of dichotomous categorical animal-based welfare indicators and the presence of two observers. Based on observations obtained from Animal Welfare Indicators (AWIN) project surveys conducted on nine dairy goat farms, and using udder asymmetry as an indicator, we compared the performance of the most popular agreement indexes available in the literature: Scott’s π, Cohen’s k, kPABAK, Holsti’s H, Krippendorff’s α, Hubert’s Γ, Janson and Vegelius’ J, Bangdiwala’s B, Andrés and Marzo’s ∆, and Gwet’s γ(AC1). Confidence intervals were calculated using closed formulas of variance estimates for π, k, kPABAK, H, α, Γ, J, ∆, and γ(AC1), while the bootstrap and exact bootstrap methods were used for all the indexes. All the indexes and closed formulas of variance estimates were calculated using Microsoft Excel. The bootstrap method was performed with R software, while the exact bootstrap method was performed with SAS software. k, π, and α exhibited a paradoxical behavior, showing unacceptably low values even in the presence of very high concordance rates. B and γ(AC1) showed values very close to the concordance rate, independently of its value. Both bootstrap and exact bootstrap methods turned out to be simpler compared to the implementation of closed variance formulas and provided effective confidence intervals for all the considered indexes. The best approach for measuring IOR in these cases is the use of B or γ(AC1), with bootstrap or exact bootstrap methods for confidence interval calculation.

EXPRESS: A meta-analysis of aspirin and subarachnoid haemorrhage in patients with intracranial aneurysms yields different results to the general population

2021 ◽  
pp. 174749302110048
Author(s):  
Frederick Ewbank ◽  
Jacqueline Birks ◽  
Diederik Bulters
Keyword(s):  
General Population ◽  
Subarachnoid Haemorrhage ◽  
Confidence Intervals ◽  
Random Effects ◽  
Intracranial Aneurysms ◽  
Meta Analysis ◽  
Risk Of Bias ◽  
Random Effects Models ◽  
Hazard Ratios ◽  
Unruptured Intracranial Aneurysms

Abstract Background Some studies have shown a protective association between aspirin use and subarachnoid haemorrhage (SAH). Other studies have found no relationship or the reverse. These studies differ in their study populations and definitions of SAH. Aims Our aim was to establish 1) if there is an association between aspirin and SAH, 2) how this differs between the general population and those with intracranial aneurysms. Summary of review Studies reporting aspirin use and the occurrence of SAH were included and grouped based on population (general population vs aneurysm population). Odds ratios, hazard ratios and confidence intervals were combined in random-effects models. 11 studies were included. Overall, there was an association between aspirin and SAH (OR 0.68 [0.48, 0.96]). However, populations were diverse and heterogeneity between studies high (p<0.00001), questioning the validity of combining these studies and justifying analysis by population. In the general population there was no difference in aspirin use between individuals with and without SAH (OR 1.15 [0.96, 1.38]). In patients with intracranial aneurysms, aspirin use was greater in patients without SAH (OR 0.37 [0.24, 0.58]), although these studies were at higher risk of bias. Conclusions There is an association between aspirin use and SAH in patients with intracranial aneurysms. This apparent protective relationship is not seen in the general population. Prospective randomised studies are required to further investigate the effect of aspirin on unruptured intracranial aneurysms.

Validation of forest height–age models

1996 ◽  
Vol 26 (5) ◽  
pp. 810-818 ◽  
Author(s):  
Gordon D. Nigh ◽  
Vera Sit
Keyword(s):  
Forest Management ◽  
Confidence Intervals ◽  
Error Variance ◽  
Site Index ◽  
Random Coefficients ◽  
Multivariate Technique ◽  
Forest Height ◽  
Preliminary Validation ◽  
Age Model ◽  
Validation Procedure

Forest height–age models are used in forest management to estimate height and (or) site index. It is useful to know the bias and precision of these models in order to evaluate their applicability. Methods are available for validating the models; however, many problems exist with the methods because of a lack of independence in the data and nonconstant error variance across a range of ages. A validation procedure is presented that overcomes these problems by using a multivariate technique (random coefficients) to model the structure of the errors associated with the models. Confidence intervals for bias and precision can then be constructed based on the error structure. This method of validation was demonstrated on the white spruce (Piceaglauca (Moench) Voss) height–age model for British Columbia, Canada. The preliminary validation showed the model to be unbiased for estimating both height and site index; however, its precision was poor.

Abstract 3789: Nessun Dorma : Have the Risks of Rosiglitazone been Exaggerated?

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
George A Diamond ◽  
Sanjay Kaul
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Cardiovascular Death ◽  
Sensitivity Analyses ◽  
Odds Ratios ◽  
True Effect Size ◽  
Index Study ◽  
The Stability

Background A highly publicized meta-analysis of 42 clinical trials comprising 27,844 diabetics ignited a firestorm of controversy by charging that treatment with rosiglitazone was associated with a “…worrisome…” 43% greater risk of myocardial infarction ( p =0.03) and a 64% greater risk of cardiovascular death ( p =0.06). Objective The investigators excluded 4 trials from the infarction analysis and 19 trials from the mortality analysis in which no events were observed. We sought to determine if these exclusions biased the results. Methods We compared the index study to a Bayesian meta-analysis of the entire 42 trials (using odds ratio as the measure of effect size) and to fixed-effects and random-effects analyses with and without a continuity correction that adjusts for values of zero. Results The odds ratios and confidence intervals for the analyses are summarized in the Table . Odds ratios for infarction ranged from 1.43 to 1.22 and for death from 1.64 to 1.13. Corrected models resulted in substantially smaller odds ratios and narrower confidence intervals than did uncorrected models. Although corrected risks remain elevated, none are statistically significant (*p<0.05). Conclusions Given the fragility of the effect sizes and confidence intervals, the charge that roziglitazone increases the risk of adverse events is not supported by these additional analyses. The exaggerated values observed in the index study are likely the result of excluding the zero-event trials from analysis. Continuity adjustments mitigate this error and provide more consistent and reliable assessments of true effect size. Transparent sensitivity analyses should therefore be performed over a realistic range of the operative assumptions to verify the stability of such assessments especially when outcome events are rare. Given the relatively wide confidence intervals, additional data will be required to adjudicate these inconclusive results.

scholarly journals Confidence Intervals for Heterogeneity Measures in Meta-analysis

2013 ◽  
Vol 178 (6) ◽  
pp. 993-1004 ◽  
Author(s):  
B. Takkouche ◽  
P. Khudyakov ◽  
J. Costa-Bouzas ◽  
D. Spiegelman
Keyword(s):  
Confidence Intervals ◽  
Meta Analysis

scholarly journals Estimating perimeter using graph cuts

2017 ◽  
Vol 49 (4) ◽  
pp. 1067-1090 ◽  
Author(s):  
Nicolás García Trillos ◽  
Dejan Slepčev ◽  
James von Brecht
Keyword(s):  
Confidence Intervals ◽  
Error Estimates ◽  
Approximation Error ◽  
Higher Dimensions ◽  
Geometric Graph ◽  
Graph Cut ◽  
Average Degree ◽  
Random Geometric Graph ◽  
Low Dimensions ◽  
Variance Estimates

Abstract We investigate the estimation of the perimeter of a set by a graph cut of a random geometric graph. For Ω ⊆ D = (0, 1)d with d ≥ 2, we are given n random independent and identically distributed points on D whose membership in Ω is known. We consider the sample as a random geometric graph with connection distance ε > 0. We estimate the perimeter of Ω (relative to D) by the, appropriately rescaled, graph cut between the vertices in Ω and the vertices in D ∖ Ω. We obtain bias and variance estimates on the error, which are optimal in scaling with respect to n and ε. We consider two scaling regimes: the dense (when the average degree of the vertices goes to ∞) and the sparse one (when the degree goes to 0). In the dense regime, there is a crossover in the nature of the approximation at dimension d = 5: we show that in low dimensions d = 2, 3, 4 one can obtain confidence intervals for the approximation error, while in higher dimensions one can obtain only error estimates for testing the hypothesis that the perimeter is less than a given number.

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