scholarly journals Understanding tree failure—A systematic review and meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246805
Author(s):  
Marinus van Haaften ◽  
Yili Liu ◽  
Yuxin Wang ◽  
Yueyue Zhang ◽  
Cornelis Gardebroek ◽  
...  
Keyword(s):  
Bayes Factor ◽  
Meta Analysis ◽  
Urban Trees ◽  
Effect Sizes ◽  
Physical Factors ◽  
P Values ◽  
Different Types ◽  
Funnel Plots ◽  
Regression Tests ◽  
Stem Failure

Recent research has indicated an increase in the likelihood and impact of tree failure. The potential for trees to fail relates to various biomechanical and physical factors. Strikingly, there seems to be an absence of tree risk assessment methods supported by observations, despite an increasing availability of variables and parameters measured by scientists, arborists and practitioners. Current urban tree risk assessments vary due to differences in experience, training, and personal opinions of assessors. This stresses the need for a more objective method to assess the hazardousness of urban trees. The aim of this study is to provide an overview of factors that influence tree failure including stem failure, root failure and branch failure. A systematic literature review according to the PRISMA guidelines has been performed in databases, supported by backward referencing: 161 articles were reviewed revealing 142 different factors which influenced tree failure. A meta-analysis of effect sizes and p-values was executed on those factors which were associated directly with any type of tree failure. Bayes Factor was calculated to assess the likelihood that the selected factors appear in case of tree failure. Publication bias was analysed visually by funnel plots and results by regression tests. The results provide evidence that the factors Height and Stem weight positively relate to stem failure, followed by Age, DBH, DBH squared times H, and Cubed DBH (DBH3) and Tree weight. Stem weight and Tree weight were found to relate positively to root failure. For branch failure no relating factors were found. We recommend that arborists collect further data on these factors. From this review it can further be concluded that there is no commonly shared understanding, model or function available that considers all factors which can explain the different types of tree failure. This complicates risk estimations that include the failure potential of urban trees.

scholarly journals Coinfections with Bacteria, Fungi, and Respiratory Viruses in Patients with SARS-CoV-2: A Systematic Review and Meta-Analysis

Pathogens ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 809
Author(s):  
Saad Alhumaid ◽  
Abbas Al Mutair ◽  
Zainab Al Alawi ◽  
Abeer M. Alshawi ◽  
Salamah A. Alomran ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cohort Studies ◽  
Visual Inspection ◽  
Fungal Infections ◽  
Meta Analysis ◽  
Case Series ◽  
Respiratory Viruses ◽  
Effect Sizes ◽  
P Values ◽  
Funnel Plots

Background: Coinfection with bacteria, fungi, and respiratory viruses in SARS-CoV-2 is of particular importance due to the possibility of increased morbidity and mortality. In this meta-analysis, we calculated the prevalence of such coinfections. Methods: Electronic databases were searched from 1 December 2019 to 31 March 2021. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses. Results: Of the 6189 papers that were identified, 72 articles were included in the systematic review (40 case series and 32 cohort studies) and 68 articles (38 case series and 30 cohort studies) were included in the meta-analysis. Of the 31,953 SARS-CoV-2 patients included in the meta-analysis, the overall pooled proportion who had a laboratory-confirmed bacterial infection was 15.9% (95% CI 13.6–18.2, n = 1940, 49 studies, I2 = 99%, p < 0.00001), while 3.7% (95% CI 2.6–4.8, n = 177, 16 studies, I2 = 93%, p < 0.00001) had fungal infections and 6.6% (95% CI 5.5–7.6, n = 737, 44 studies, I2 = 96%, p < 0.00001) had other respiratory viruses. SARS-CoV-2 patients in the ICU had higher co-infections compared to ICU and non-ICU patients as follows: bacterial (22.2%, 95% CI 16.1–28.4, I2 = 88% versus 14.8%, 95% CI 12.4–17.3, I2 = 99%), and fungal (9.6%, 95% CI 6.8–12.4, I2 = 74% versus 2.7%, 95% CI 0.0–3.8, I2 = 95%); however, there was an identical other respiratory viral co-infection proportion between all SARS-CoV-2 patients [(ICU and non-ICU) and the ICU only] (6.6%, 95% CI 0.0–11.3, I2 = 58% versus 6.6%, 95% CI 5.5–7.7, I2 = 96%). Funnel plots for possible publication bias for the pooled effect sizes of the prevalence of coinfections was asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry (p values < 0.05). Conclusion: Bacterial co-infection is relatively high in hospitalized patients with SARS-CoV-2, with little evidence of S. aureus playing a major role. Knowledge of the prevalence and type of co-infections in SARS-CoV-2 patients may have diagnostic and management implications.

The effect of 0.01% atropine on ocular axial elongation for myopia children: a meta-analysis

2021 ◽  
Author(s):  
Yan Yu ◽  
Jiasu Liu
Keyword(s):  
Publication Bias ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Cochrane Library ◽  
Axial Elongation ◽  
Funnel Plots ◽  
Mean Differences ◽  
Q Statistic ◽  
Regression Tests ◽  
Review Manager

Objectives: This meta-analysis aimed to identify the therapeutic effect of 0.01% atropine with on ocular axial elongation for myopia children. Methods: We searched PubMed, Cochrane Library, and CBM databases from inception to July 2021. Meta-analysis was conducted using STATA version 14.0 and Review Manager version 5.3 softwares. We calculated the weighted mean differences(WMD) to analyze the change of ocular axial length (AL) between orthokeratology combined with 0.01% atropine (OKA) and orthokeratology (OA) alone. The Cochran's Q-statistic and I2 test were used to evaluate potential heterogeneity between studies. To evaluate the influence of single studies on the overall estimate, a sensitivity analysis was performed. We also performed sub group and meta-regression analyses to investigate potential sources of heterogeneity. We conducted Begger's funnel plots and Egger's linear regression tests to investigate publication bias. Results: Nine studies that met all inclusion criteria were included in this meta-analysis. A total of 191 children in OKA group and 196 children in OK group were assessed. The pooled summary WMD of AL change was -0.90(95%CI=-1.25~-0.55) with statistical significance(t=-5.03, p<0.01), which indicated there was obvious difference between OKA and OK in myopic children. Subgroup analysis also showed that OKA treatment resulted in significantly less axial elongation compared to OK treatment alone according to SER. We found no evidence for publication bias. Conclusions:  Our meta-analysis indicates 0.01% atropine atropine is effective in slowing axial elongation in myopia children with orthokeratology.

scholarly journals A Statistical Method for Synthesizing Meta-Analyses

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman
Keyword(s):  
Statistical Method ◽  
Effect Size ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Weighted Mean ◽  
Summary Effect ◽  
Different Types ◽  
Meta Analyses ◽  
Size Estimates ◽  
Similar Search

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.

scholarly journals The Galaxy Plot: A New Visualization Tool for Bivariate Meta-Analysis Studies

2020 ◽  
Vol 189 (8) ◽  
pp. 861-869 ◽  
Author(s):  
Chuan Hong ◽  
Rui Duan ◽  
Lingzhen Zeng ◽  
Rebecca A Hubbard ◽  
Thomas Lumley ◽  
...  
Keyword(s):  
Dimensional Space ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Standard Errors ◽  
Visualization Tool ◽  
The Galaxy ◽  
Funnel Plots ◽  
Complex Features ◽  
Bivariate Outcomes ◽  
Meta Analyses

Abstract Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing visualization tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979–1991 (Hypertension. 2005;45(5):907–913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966–2015 (Heart. 2017;103(4):255–257). The galaxy plot is an intuitive visualization tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.

Meta-analysis: A 12-step program

2003 ◽  
Author(s):  
L. Streiner David
Keyword(s):  
Meta Analysis ◽  
Effect Sizes ◽  
Prevalence Rates ◽  
Global Estimate ◽  
Different Types ◽  
Comprehensive Search ◽  
Meta Analyses ◽  
Explicit Criteria ◽  
Step Program

Meta-analysis is a technique for combining the results of many studies in a rigorous and systematic manner, to allow us to better assess prevalence rates for different types of gambling and determine which interventions have the best evidence regarding their effectiveness and efficacy. Meta-analysis consists of (a) a comprehensive search for all available evidence; (b) the use of applying explicit criteria for determining which articles to include; (c) determination of an effect size for each study; and (d) the pooling of effect sizes across studies to end up with a global estimate of the prevalence or the effectiveness of a treatment. This paper begins with a discussion of why meta-analyses are useful, followed by a 12-step program for conducting a meta-analysis. This program can be used both by people planning to do such an analysis, as well as by readers of a meta-analysis, to evaluate how well it was carried out.

A Meta-Analysis of the Efficacy of Different Types of Parental Involvement Programs for Urban Students

2012 ◽  
Vol 47 (4) ◽  
pp. 706-742 ◽  
Author(s):  
William Jeynes
Keyword(s):  
Academic Achievement ◽  
Parental Involvement ◽  
Secondary School ◽  
Secondary School Students ◽  
Meta Analysis ◽  
Effect Sizes ◽  
School Students ◽  
12Th Grade ◽  
Different Types ◽  
The Relationship

This meta-analysis of 51 studies examines the relationship between various kinds of parental involvement programs and the academic achievement of pre-kindergarten-12th-grade school children. Analyses determined the effect sizes for various parental involvement programs overall and subcategories of involvement. Results indicate a significant relationship between parental involvement programs overall and academic achievement, both for younger (preelementary and elementary school) and older (secondary school) students as well as for four types of parental involvement programs. Parental involvement programs, as a whole, were associated with higher academic achievement by .3 of a standard deviation unit. The significance of these results is discussed.

scholarly journals Role of Meta-analysis in Interpreting the Scientific Literature

2013 ◽  
Author(s):  
Michael D. Jennions ◽  
Christopher J. Lortie ◽  
Julia Koricheva
Keyword(s):  
Statistical Power ◽  
Scientific Literature ◽  
Meta Analysis ◽  
Effect Sizes ◽  
P Values ◽  
Single Study ◽  
Broad Scale

This chapter begins with a brief review of why effect sizes and their variances are more informative than P-values. It then discusses how meta-analysis promotes “effective thinking” that can change approaches to several commonplace problems. Specifically, it addresses the issues of (1) exemplar studies versus average trends, (2) resolving “conflict” between specific studies, (3) presenting results, (4) deciding on the level at which to replicate studies, (5) understanding the constraints imposed by low statistical power, and (6) asking broad-scale questions that cannot be resolved in a single study. The chapter focuses on estimating effect sizes as a key outcome of meta-analysis, but acknowledges that other outcomes might be of more interest in other situations.

scholarly journals Social Support Benefits Psychological Adjustment of International Students: Evidence From a Meta-Analysis

2019 ◽  
Vol 50 (7) ◽  
pp. 827-847 ◽  
Author(s):  
Michael Bender ◽  
Yvette van Osch ◽  
Willem Sleegers ◽  
Mengyu Ye
Keyword(s):  
Social Support ◽  
International Students ◽  
Psychological Adjustment ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Future Research ◽  
Systematic Assessment ◽  
Growing Body ◽  
Different Types ◽  
The Relationship

A growing body of literature is exploring the link between social support and international students’ psychological adjustment. So far, however, there has been no systematic assessment of the overall relationship, and no indication which types and sources of social support may be most strongly associated with psychological adjustment. Our meta-analysis of 257 effect sizes across 76 studies fills this gap and assesses (a) the magnitude of the overall association between social support and international students’ psychological adjustment, (b) how different types (subjective, objective, and mixed) and sources (host, conational, international, mixed, and unspecified) of social support moderate the relationship between social support and psychological adjustment, and (c) whether the relationship between social support and psychological adjustment holds across different operationalizations of psychological adjustment. We find a positive overall association ( r = .20, 95% confidence interval [CI] = [0.16, 0.23]) between social support and international students’ psychological adjustment. Types and sources of social support matter as well: Subjective social support relates more strongly to psychological adjustment than objective social support. The data revealed that only support from mixed sources (i.e., not distinguishing between internationals, host, or conationals) is associated with a stronger effect of social support than support from conationals or from fellow international students (compared with support from host sources). We find no differences in the relation between social support and positive or negative adjustment. We outline recommendations for future research based on the meta-analysis.

scholarly journals Big Five and HEXACO Personality Traits, Proenvironmental Attitudes, and Behaviors: A Meta-Analysis

2020 ◽  
Vol 15 (4) ◽  
pp. 913-941 ◽  
Author(s):  
Alistair Raymond Bryce Soutter ◽  
Timothy C. Bates ◽  
René Mõttus
Keyword(s):  
Climate Change ◽  
Personality Traits ◽  
Big Five ◽  
Predictive Accuracy ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Gender Ratio ◽  
Attitudes And Behaviors ◽  
Funnel Plots ◽  
And Behaviors

With climate change and its consequences believed to be among the most vital challenges for humanity and the Earth’s ecosystem, it is important to understand why individuals do or do not adopt proenvironmental attitudes and behaviors. Personality traits are well suited for this purpose. Because no recent work has systematically combined the accumulating evidence on this topic, we aimed to meta-analyze the associations of the Big Five and HEXACO personality domains with proenvironmental attitudes and behaviors. A meta-analysis of 38 sources ( N = 44,993) implicated openness and honesty-humility as the strongest correlates of proenvironmental attitudes ( r = .22 and .20) and behaviors ( r = .21 and .25). Agreeableness, conscientiousness, and, to a lesser extent, extraversion were also associated with proenvironmental attitudes ( r = .15, .12, and .09) and behaviors ( r = .10, .11, and .10). Heterogeneity among effect sizes was partly explained by samples’ gender ratio, age, and country of origin and by the personality model. P-curve analyses, funnel plots, and Egger’s tests indicated significant but sporadic and small publication bias. As a validity test, the meta-analytic associations collectively provided substantial predictive accuracy for proenvironmental attitudes ( r = .44–.45) and behaviors ( r = .28–.43) in independent holdout samples.

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