Graphical Presentation of Results

2013 ◽  
Author(s):  
Christopher J. Lortie ◽  
Joseph Lau ◽  
Marc J. Lajeunesse
Keyword(s):  
Evolutionary Biology ◽  
Meta Analysis ◽  
Statistical Technique ◽  
The Social ◽  
Error Bar ◽  
Funnel Plots ◽  
Meta Analyses ◽  
Main Effects ◽  
The Relationship ◽  
Graphical Presentation

Visualizations of data are one of the most compelling means to effectively communicate ideas in science. Graphs present data in a visual form enabling the reader to read values, identify patterns, assess the outcome of a statistical technique, or analyze relationships within or between variables. Effective visualizations of meta-analyses have been discussed extensively in the evidence-based medical literature and to a lesser extent in ecology and evolutionary biology. The two most common meta-analysis plots are derived from the social sciences and include (1) modified error bar plots called forest plots used to summarize and compare weighted mean effects, and (2) meta-regression plots (scatterplots with significant fit lines) used to show the relationship between main effects and covariates. This chapter describes these two standard meta-analysis plots and provides sample graphics to illustrate usage. Details are also included for the use of simple histograms and funnel plots.

scholarly journals Temporal Trends in Effect Sizes: Causes, Detection, and Implications

2013 ◽  
Author(s):  
Julia Koricheva ◽  
Michael D. Jennions ◽  
Joseph Lau
Keyword(s):  
Evolutionary Biology ◽  
Meta Analysis ◽  
Scientific Evidence ◽  
Temporal Trends ◽  
Temporal Changes ◽  
Effect Sizes ◽  
The Social ◽  
The Stability ◽  
Meta Analyses ◽  
Over Time

The general aim of meta-analysis is to combine scientific evidence scattered through a number of individual studies addressing the same topic. Evidence, however, is not static and tends to evolve over time due to changes in research methods, changes in the characteristics of the subjects being studied, for example. A number of recent studies in ecology and evolution have shown that temporal trends in effect sizes are common and often quite dramatic in these fields. Temporal changes in effect sizes could jeopardize the stability of conclusions (i.e., the conclusions of meta-analyses on the same topic conducted in different years might differ). For these reasons, this chapter is devoted to temporal changes in effect sizes. It first summarizes the findings of studies that examined temporal changes in the magnitude and direction of effect sizes in ecology, evolutionary biology, medicine, and the social sciences. It then discusses their possible causes, methods of detection, and implications for the interpretation of the results of the meta-analysis.

A Meta-Analysis of Interviews and Cognitive Ability

2013 ◽  
Vol 12 (4) ◽  
pp. 157-169 ◽  
Author(s):  
Philip L. Roth ◽  
Allen I. Huffcutt
Keyword(s):  
Cognitive Ability ◽  
Meta Analysis ◽  
Incremental Validity ◽  
Employment Interviews ◽  
Moderator Analysis ◽  
The Future ◽  
Research Questions ◽  
Meta Analyses ◽  
The Relationship

The topic of what interviews measure has received a great deal of attention over the years. One line of research has investigated the relationship between interviews and the construct of cognitive ability. A previous meta-analysis reported an overall corrected correlation of .40 ( Huffcutt, Roth, & McDaniel, 1996 ). A more recent meta-analysis reported a noticeably lower corrected correlation of .27 ( Berry, Sackett, & Landers, 2007 ). After reviewing both meta-analyses, it appears that the two studies posed different research questions. Further, there were a number of coding judgments in Berry et al. that merit review, and there was no moderator analysis for educational versus employment interviews. As a result, we reanalyzed the work by Berry et al. and found a corrected correlation of .42 for employment interviews (.15 higher than Berry et al., a 56% increase). Further, educational interviews were associated with a corrected correlation of .21, supporting their influence as a moderator. We suggest a better estimate of the correlation between employment interviews and cognitive ability is .42, and this takes us “back to the future” in that the better overall estimate of the employment interviews – cognitive ability relationship is roughly .40. This difference has implications for what is being measured by interviews and their incremental validity.

Power-Enhanced Funnel Plots for Meta-Analysis

2020 ◽  
Vol 228 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Relevant Information ◽  
Selective Reporting ◽  
Graphical Display ◽  
Funnel Plot ◽  
Evidential Value ◽  
Graphical Displays ◽  
Funnel Plots ◽  
Meta Analyses

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.

Career Adaptability and Career Decision Self-Efficacy: Meta-Analysis

2021 ◽  
pp. 089484532110124
Author(s):  
Graham B. Stead ◽  
Lindsey M. LaVeck ◽  
Sandra M. Hurtado Rúa
Keyword(s):  
Self Efficacy ◽  
Total Population ◽  
Meta Analysis ◽  
Career Decision ◽  
Decision Making Process ◽  
Career Adaptability ◽  
Efficacy Measures ◽  
Meta Analyses ◽  
Career Research ◽  
The Relationship

The relationship between career adaptability and career decision self-efficacy was examined due to its importance for clients in the career development and career decision-making process. Multivariate meta-analyses using 18 studies with a total population of 6,339 participants were employed. Moderator variables important to this relationship were country of participants, mean age, and career adaptability measures. Estimated correlations between career adaptability subscales and career decision self-efficacy measures ranged from .36 to .44. Findings are discussed in relation to career research and counseling.

scholarly journals Resting Heart Rate as a Predictor of Cancer Mortality: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 10 (7) ◽  
pp. 1354
Author(s):  
Diana P. Pozuelo-Carrascosa ◽  
Iván Cavero-Redondo ◽  
I.M. Lee ◽  
Celia Álvarez-Bueno ◽  
Sara Reina-Gutierrez ◽  
...  
Keyword(s):  
Heart Rate ◽  
Cancer Mortality ◽  
Meta Analysis ◽  
Positive Association ◽  
Cochrane Library ◽  
Resting Heart Rate ◽  
Potential Marker ◽  
Meta Analyses ◽  
Risk Of Cancer ◽  
The Relationship

This work was aimed to synthetize the evidence available about the relationship between resting heart rate (RHR) and the risk of cancer mortality. A computerized search in the Medline, EMBASE, Web of Science, and Cochrane Library databases from their inception to 24 September 2020 was performed. We performed three meta-analyses: (1) cancer mortality comparing the “less than 60 bpm” and “more than 60 bpm” categories; (2) cancer mortality comparing “less than 60 bpm”, “60 to 80 bpm”, and “more than 80 bpm” categories; and (3) analysis for 10–12 and 20 bpm increase in RHR and risk of cancer mortality. Twenty-two studies were included in the qualitative review, and twelve of them met the inclusion criteria for the meta-analysis. Our results showed a positive association between RHR and the risk of cancer mortality. This association was shown in a meta-analysis comparing studies reporting mean RHR values below and above 60 bpm, when comparing three RHR categories using less than 60 bpm as the reference category and, finally, in dose response analyses estimating the effect of an increase of 10–12 bpm in RHR, both in men and in women. In conclusion, a low RHR is a potential marker of low risk of cancer mortality.

scholarly journals Osteoarthritis, mobility-related comorbidities and mortality: an overview of meta-analyses

2020 ◽  
Vol 12 ◽  
pp. 1759720X2098121
Author(s):  
Gustavo Constantino de Campos ◽  
Raman Mundi ◽  
Craig Whittington ◽  
Marie-Josée Toutounji ◽  
Wilson Ngai ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Inclusion Criteria ◽  
Increased Risk ◽  
All Cause Mortality ◽  
Ischemic Attack ◽  
Meta Analyses ◽  
The Relationship ◽  
Related Mortality

Aims: The objective of this review was to examine the relationship between osteoarthritis (OA) and mobility-related comorbidities, specifically diabetes mellitus (DM) and cardiovascular disease (CVD). It also investigated the relationship between OA and mortality. Methods: An overview of meta-analyses was conducted by performing two targeted searches from inception to June 2020. The association between OA and (i) DM or CVD ( via PubMed and Embase); and (ii) mortality ( via PubMed) was investigated. Meta-analyses were selected if they included studies that examined adults with OA at any site and reported associations between OA and DM, CVD, or mortality. Evidence was synthesized qualitatively. Results: Six meta-analyses met inclusion criteria. One meta-analysis of 20 studies demonstrated a statistically significant association between OA and DM, with pooled odds ratio of 1.41 (95% confidence interval: 1.21, 1.65; n = 1,040,175 patients). One meta-analysis of 15 studies demonstrated significantly increased risk of CVD among OA patients, with a pooled risk ratio of 1.24 (1.12, 1.37, n = 358,944 patients). Stratified by type of CVD, OA was shown to be associated with increased heart failure (HF) and ischemic heart disease (IHD) and reduced transient ischemic attack (TIA). There was no association reported for stroke or myocardial infarction (MI). Three meta-analyses did not find a significant association between OA (any site) and all-cause mortality. However, OA was found to be significantly associated with cardiovascular-related death across two meta-analyses. Conclusion: The identified meta-analyses reported significantly increased risk of both DM and CVD (particularly, HF and IHD) among OA patients. It was not possible to confirm consistent directional or causal relationships. OA was found to be associated with increased mortality, but mostly in relation to CVD-related mortality, suggesting that further study is warranted in this area.

scholarly journals Low birth weight, preterm birth and small for gestational age association with adult depression: systematic review and meta-analysis

2014 ◽  
Vol 205 (5) ◽  
pp. 340-347 ◽  
Author(s):  
Christian Loret De Mola ◽  
Giovanny Vinícius Araújo De França ◽  
Luciana de Avila Quevedo ◽  
Bernardo Lessa Horta
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Gestational Age ◽  
Premature Birth ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Adult Depression ◽  
Meta Analyses ◽  
Relationship Of ◽  
The Relationship

BackgroundThere is no consensus on the effects that low birth weight, premature birth and intrauterine growth have on later depression.AimsTo review systematically the evidence on the relationship of low birth weight, smallness for gestational age (SGA) and premature birth with adult depression.MethodWe searched the literature for original studies assessing the effect of low birth weight, premature birth and SGA on adult depression. Separate meta-analyses were carried out for each exposure using random and fixed effects models. We evaluated the contribution of methodological covariates to heterogeneity using meta-regression.ResultsWe identified 14 studies evaluating low birth weight, 9 premature birth and 4 SGA. Low birth weight increased the odds of depression (OR = 1.39, 95% CI 1.21–1.60). Premature birth and SGA were not associated with depression, but publication bias might have underestimated the effect of the former and only four studies evaluated SGA.ConclusionsLow birth weight was associated with depression. Future studies evaluating premature birth and SGA are needed.

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.

scholarly journals Psychiatric Manifestations of Coeliac Disease, a Systematic Review and Meta-Analysis

Nutrients ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 142 ◽  
Author(s):  
Emma Clappison ◽  
Marios Hadjivassiliou ◽  
Panagiotis Zis
Keyword(s):  
Systematic Review ◽  
Eating Disorders ◽  
Coeliac Disease ◽  
Psychiatric Disorders ◽  
Meta Analysis ◽  
Hyperactivity Disorder ◽  
Increased Risk ◽  
Meta Analyses ◽  
Psychiatric Manifestations ◽  
The Relationship

Background: Coeliac disease (CD) is increasingly prevalent and is associated with both gastrointestinal (GI) and extra-intestinal manifestations. Psychiatric disorders are amongst extra-intestinal manifestations proposed. The relationship between CD and such psychiatric disorders is not well recognised or understood. Aim: The aim of this systematic review and meta-analysis was to provide a greater understanding of the existing evidence and theories surrounding psychiatric manifestations of CD. Methodology: An online literature search using PubMed was conducted, the prevalence data for both CD and psychiatric disorders was extracted from eligible articles. Meta analyses on odds ratios were also performed. Results: A total of 37 articles were included in this review. A significant increase in risk was detected for autistic spectrum disorder (OR 1.53, 95% CI 1.24–1.88, p < 0.0001), attention deficit hyperactivity disorder (OR 1.39, 95% CI 1.18–1.63, p < 0.0001), depression (OR 2.17, 95% CI 2.17–11.15, p < 0.0001), anxiety (OR 6.03, 95% CI 2.22–16.35, p < 0.0001), and eating disorders (OR 1.62, 95% CI 1.37–1.91, p < 0.00001) amongst the CD population compared to healthy controls. No significant differences were found for bipolar disorder (OR 2.35, 95% CI 2.29–19.21, p = 0.43) or schizophrenia (OR 0.46, 95% CI 0.02–10.18, p = 0.62). Conclusion: CD is associated with an increased risk of depression, anxiety, eating disorders as well as ASD and ADHD. More research is required to investigate specific biological explanations as well as any effect of gluten free diet.

Inferring prior distributions of recruitment compensation metrics from life-history parameters and allometries

2020 ◽  
Vol 77 (2) ◽  
pp. 295-313 ◽  
Author(s):  
Joseph Munyandorero
Keyword(s):  
Life Histories ◽  
Growth Parameters ◽  
Meta Analysis ◽  
The United States ◽  
Prior Distributions ◽  
Compensation Ratio ◽  
Species Specific ◽  
Meta Analyses ◽  
The Relationship ◽  
Spawning Biomass

The recruitment compensation metrics, the stock–recruit steepness (h) and compensation ratio (κ), are difficult to estimate, yet they are integral components of contemporary fishery models. To aid in the estimation of κ and h, a hybrid method to construct their prior distributions for a species is developed. The method is hybrid because it integrates (i) a meta-analysis of the relationship between maximum rates of recruit production (α) and asymptotic lengths obtained across fish species of different life histories and (ii) species-specific unfished spawning biomass per recruit (Φ0). This method is applied to five finfish species found off the East Coast of the United States. Uncertainty is introduced by sampling growth parameters, α, and natural mortality and — through Monte Carlo simulations — propagated into Φ0, κ, and h for the Beverton–Holt and Ricker stock–recruit relationships. Descriptive statistics and parameters from probability density functions of the simulated distributions of κ and h are generated. The method developed requires fewer inputs than the reproductive ecology method while likewise allowing the development of species-specific statistics for κ and h. These statistics, rather than their counterparts generated from classical meta-analyses, are better suited for use in fishery models.

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