A note on the empirical Bayes heterogeneity variance estimator in meta‐analysis

2019 ◽  
Vol 38 (20) ◽  
pp. 3804-3816 ◽  
Author(s):  
Kurex Sidik ◽  
Jeffrey N. Jonkman
Keyword(s):  
Empirical Bayes ◽  
Meta Analysis ◽  
Variance Estimator ◽  
Heterogeneity Variance

Factor XIII Val34Leu variant protects against coronary artery disease

2007 ◽  
Vol 97 (03) ◽  
pp. 458-463 ◽  
Author(s):  
Zsuzsanna Bereczky ◽  
Éva Katona ◽  
Róza Ádány ◽  
László Muszbek ◽  
Zoltán Vokó
Keyword(s):  
Myocardial Infarction ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Protective Effect ◽  
Factor Xiii ◽  
Empirical Bayes ◽  
Meta Analysis ◽  
Environmental Interactions ◽  
History Of ◽  
Artery Disease

SummarySeveral studies suggested that Val34Leu variant of factor XIII (FXIII) might have a protective effect against coronary artery disease (CAD), but studies not supporting these findings have also been published. The authors performed a meta-analysis of 16 studies on 5,346 cases and 7,053 controls that investigated the association between Val34Leu polymorphism and CAD defined as history of myocardial infarction or significant stenosis on a coronary artery assessed by coronary angiography. Because of the heterogeneity of the study-specific results, the pooled effect estimates were calculated by a random-effects empirical Bayes model. The combined odds ratios for CAD were 0.82 (95% confidence interval [95% Cl] 0.73, 0.94) for the heterozygotes of the FXIIIVal34Leu variant, 0.89 (95% CI 0.69, 1.13) for the homozygotes, and 0.81 (95% CI 0.70, 0.92) for the heterozygotes and homozygotes combined. The results were essentially the same when only myocardial infarction was considered as outcome. The beneficial effect of the polymorphism might be smaller than the effect estimates obtained in this metaanalysis, because the analysis raised the possibility of publication bias. Data published in the literature suggest that gene-gene and gene-environmental interactions might significantly influence the protective effect of FXIII-AVal34Leu polymorphism.

Empirical Bayes Methods in Clinical Trials Meta-Analysis

2007 ◽  
Vol 32 (3) ◽  
pp. 335-346 ◽  
Author(s):  
Th. Stijnen ◽  
J. C. Van Houwelingen
Keyword(s):  
Clinical Trials ◽  
Empirical Bayes ◽  
Meta Analysis ◽  
Bayes Methods ◽  
Empirical Bayes Methods

What is the carrying capacity for fish in the ocean? A meta-analysis of population dynamics of North Atlantic cod

2001 ◽  
Vol 58 (7) ◽  
pp. 1464-1476 ◽  
Author(s):  
Ransom A Myers ◽  
Brian R MacKenzie ◽  
Keith G Bowen ◽  
Nicholas J Barrowman
Keyword(s):  
North Atlantic ◽  
Carrying Capacity ◽  
Empirical Bayes ◽  
Gadus Morhua ◽  
Mixed Model ◽  
Atlantic Cod ◽  
Unit Area ◽  
Meta Analysis ◽  
Reproductive Rate ◽  
Parameter Estimates

Population and community data in one study are usually analyzed in isolation from other data. Here, we introduce statistical methods that allow many data sets to be analyzed simultaneously such that different studies may "borrow strength" from each other. In the simplest case, we simultaneously model 21 Atlanic cod (Gadus morhua) stocks in the North Atlantic assuming that the maximum reproductive rate and the carrying capacity per unit area are random variables. This method uses a nonlinear mixed model and is a natural approach to investigate how carrying capacity varies among populations. We used empirical Bayes techniques to estimate the maximum reproductive rate and carrying capacity of each stock. In all cases, the empirical Bayes estimates were biologically reasonable, whereas a stock by stock analysis occasionally yielded nonsensical parameter estimates (e.g., infinite values). Our analysis showed that the carrying capacity per unit area varied by more than 20-fold among populations and that much of this variation was related to temperature. That is, the carrying capacity per square kilometre declines as temperature increases.

scholarly journals Impact of Toothbrush Age on Clinical Indicators of Oral Health, a Protocol for a Systematic Review

2021 ◽  
Author(s):  
Sepideh Zayandeh ◽  
Zahra Yaghoubi ◽  
Kosar Hosseini
Keyword(s):  
Systematic Review ◽  
Oral Health ◽  
Dental Caries ◽  
Meta Analysis ◽  
Clinical Indicators ◽  
Plaque Removal ◽  
Study Selection ◽  
Manual Toothbrush ◽  
Heterogeneity Variance ◽  
The Relationship

Abstract Background: Dental caries is the most common chronic untreated disease worldwide. The simplest and most important factor in preventing dental caries is maintaining oral hygiene and removing microbial plaque using a toothbrush. Despite the relationship between toothbrush filament wear and plaque removal effectiveness as a potentially important factor in maintaining oral health, there is little objective standard evidence as to 1) what constitutes a worn-out brush and 2) the degree of loss in plaque removal effectiveness due to brush wear. Contradictions in the results of studies on toothbrushing and the loss of its effectiveness in removing plaque based on the time spent using the toothbrush have led to conflicting recommendations for changing toothbrushes after different periods. While some studies generally question the relationship between toothbrush age and effectiveness. The lack of comprehensive evidence in this area necessitates a structured review study.Methods: We will search the electronic databases ISI, Scopus, and PubMed to find related articles. Our main inclusion criterion is Clinical trial and observational studies investigating manual toothbrush longevity in the natural toothbrush-worn model on each objective indicator of oral health (including plaque removal and gingival indices ...). All funded citations are entered into the Endnote software. the full texts of potentially relevant studies are prepared. study selection and extracting the data will be performed by two reviewers. Also, the studies quality will be assessed. The findings will be displayed using figures, summary tables and narrative summaries. If the similarity of studies and their quality is desirable, meta-analysis will be performed. We will assess the heterogeneity on the bias of the magnitude of heterogeneity variance parameter. We are also going to conduct subgroup analysis and sensitivity analysis if needed.Discussion: The final systematic review highlights the gaps in the available evidence about the effectiveness of toothbrush longevity on each oral indices to provide the best recommendation for toothbrush renewal periods. Registration: The review subject has been submitted in PROSPERO database

Empirical Bayes Meta-Analysis

1985 ◽  
Vol 10 (2) ◽  
pp. 75-98 ◽  
Author(s):  
Stephen W. Raudenbush ◽  
Anthony S. Bryk
Keyword(s):  
Quantitative Research ◽  
Empirical Bayes ◽  
Linear Models ◽  
Meta Analysis ◽  
Mixed Linear Model ◽  
Teacher Expectancy ◽  
Study Characteristics ◽  
Parameter Variance ◽  
Effect Parameter ◽  
Estimation Of Variance

As interest in quantitative research synthesis grows, investigators increasingly seek to use information about study features—study contexts, designs, treatments, and subjects—to account for variation in study outcomes. To facilitate analysis of diverse study findings, a mixed linear model with fixed and random effects is presented and illustrated with data from teacher expectancy experiments. This strategy enables the analyst to (a) estimate the variance of the effect size parameters by means of maximum likelihood; (b) pose a series of linear models to explain the effect parameter variance; (c) use information about study characteristics to derive improved empirical Bayes estimates of individual study effect sizes; and (d) examine the sensitivity of all substantive inferences to likely errors in the estimation of variance components.

Educational Applications of Hierarchical Linear Models: A Review

1988 ◽  
Vol 13 (2) ◽  
pp. 85-116 ◽  
Author(s):  
Stephen W. Raudenbush
Keyword(s):  
Linear Regression ◽  
Empirical Bayes ◽  
Linear Models ◽  
Meta Analysis ◽  
Classical Test Theory ◽  
Hierarchical Linear Models ◽  
Estimation Theory ◽  
Test Theory ◽  
Regression Coefficients ◽  
Data Sets

The search for appropriate statistical methods for hierarchical, multilevel data has been a prominent theme in educational statistics over the past 15 years. As a result of this search, an important class of models, termed hierarchical linear models by this review, has emerged. In the paradigmatic application of such models, observations within each group (e.g., classroom or school) vary as a function of group-level or “microparameters.” However, these microparameters vary randomly across the population of groups as a function of “macroparameters.” Research interest has focused on estimation of both micro- and macroparameters. This paper reviews estimation theory and application of such models. Also, the logic of these methods is extended beyond the paradigmatic case to include research domains as diverse as panel studies, meta-analysis, and classical test theory. Microparameters to be estimated may be as diverse as means, proportions, variances, linear regression coefficients, and logit linear regression coefficients. Estimation theory is reviewed from Bayes and empirical Bayes viewpoints and the examples considered involve data sets with two levels of hierarchy.

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