Estimating common mean and heterogeneity variance in two study case meta-analysis

2012 ◽  
Vol 82 (7) ◽  
pp. 1318-1325 ◽  
Author(s):  
Andrew L. Rukhin
Keyword(s):  
Meta Analysis ◽  
Common Mean ◽  
Study Case ◽  
Heterogeneity Variance

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

scholarly journals Intervensi Gizi dalam Penanganan dan Pencegahan Stunting di Asia: Tinjauan Sistematis

2020 ◽  
Vol 5 (1) ◽  
pp. 26-30
Author(s):  
Joko Tri Atmojo ◽  
Rina Tri Handayani ◽  
Aquartuti Tri Darmayanti ◽  
Catur Setyorini ◽  
Aris Widiyanto
Keyword(s):  
Controlled Trial ◽  
Meta Analysis ◽  
Nutrition Intervention ◽  
Long Term Effects ◽  
Nutrition Interventions ◽  
Verbal Abilities ◽  
Nutrition Programs ◽  
Study Case

Background: Stunting has dire consequences for children's health in the short term which can decrease cognitive, motor and verbal abilities, increase morbidity and even mortality. Nutrition intervention is absolutely necessary in efforts to reduce and prevent stunting. Purpose this study is to identify nutrition interventions in handling and preventing stunting in Asia.  Methods: This search was conducted from September to October 2019, through various databases including PubMed, EMBASE, and CINAHL. Article inclusion criteria: randomized controlled trial, retrospective, observational study, case study, review, systematc review, and meta-analysis. Results: The review results show that in Asia there were 8 specific nutrition programs and 9 sensitive nutrition programs. Conclusion: Interventions for sensitive and specific nutrition programs have been shown to reduce the incidence of stunting and address the long-term effects of stunting in various countries in Asia, but the programming and implementation can be arranged according to country needs and conditions.

scholarly journals Exploring consequences of simulation design for apparent performance of methods of meta-analysis

2021 ◽  
pp. 096228022110130
Author(s):  
Elena Kulinskaya ◽  
David C. Hoaglin ◽  
Ilyas Bakbergenuly
Keyword(s):  
Odds Ratio ◽  
Meta Analysis ◽  
Data Generation ◽  
Sample Sizes ◽  
Simulation Design ◽  
Two Stage ◽  
Inverse Variance ◽  
Log Odds ◽  
Heterogeneity Variance ◽  
The Impact

Contemporary statistical publications rely on simulation to evaluate performance of new methods and compare them with established methods. In the context of random-effects meta-analysis of log-odds-ratios, we investigate how choices in generating data affect such conclusions. The choices we study include the overall log-odds-ratio, the distribution of probabilities in the control arm, and the distribution of study-level sample sizes. We retain the customary normal distribution of study-level effects. To examine the impact of the components of simulations, we assess the performance of the best available inverse–variance–weighted two-stage method, a two-stage method with constant sample-size-based weights, and two generalized linear mixed models. The results show no important differences between fixed and random sample sizes. In contrast, we found differences among data-generation models in estimation of heterogeneity variance and overall log-odds-ratio. This sensitivity to design poses challenges for use of simulation in choosing methods of meta-analysis.

Estimation of a common mean vector in bivariate meta-analysis under the FGM copula

Statistics ◽  
2019 ◽  
Vol 53 (3) ◽  
pp. 673-695 ◽  
Author(s):  
Jia-Han Shih ◽  
Yoshihiko Konno ◽  
Yuan-Tsung Chang ◽  
Takeshi Emura
Keyword(s):  
Meta Analysis ◽  
Common Mean ◽  
Mean Vector
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