scholarly journals Meta-Analysis of the Effect of Red on Perceived Attractiveness

2018 ◽  
Vol 16 (4) ◽  
pp. 147470491880241 ◽  
Author(s):  
Gabrielle K. Lehmann ◽  
Andrew J. Elliot ◽  
Robert J. Calin-Jageman
Keyword(s):  
Meta Analysis ◽  
Effect Sizes ◽  
Future Research ◽  
Meta Analyses ◽  
Heterosexual Attraction ◽  
Substantial Heterogeneity ◽  
Over Time ◽  
Perceived Attractiveness

We conducted meta-analyses of studies that test the red-romance hypothesis, which is that the color red enhances heterosexual attraction in romantic contexts. For men rating women, we found a small, statistically significant effect ( d = 0.26 [0.12, 0.40], p = .0004, N = 2,961), with substantial heterogeneity, Q(44) = 172.5, pQ < .0001, I2 = 89% [82, 94], and equivocal results regarding the possibility of upward bias in the estimate. For women rating men, we found a very small effect ( d = 0.13 [0.01, 0.25], p = .03, N = 2,739), with substantial heterogeneity, Q(35) = 73.0, pQ = .0002, I2 = 53% [33, 80], and evidence of upward bias in the estimate. Moderator analyses suggest effect sizes may have declined over time (both genders), may be largest when an original shade of red is used (men only), and may be smaller in preregistered studies (women only). We present contrasting interpretations and suggestions for future research.

scholarly journals Variability in the Results of Meta-Analysis as a Function of Comparing Effect Sizes Based on Scores From Noncomparable Measures: A Simulation Study

2016 ◽  
Vol 77 (3) ◽  
pp. 449-470 ◽  
Author(s):  
William R. Nugent
Keyword(s):  
Fixed Effects ◽  
Meta Analysis ◽  
Monte Carlo Study ◽  
Significant Degree ◽  
Effect Sizes ◽  
Future Research ◽  
Placebo Condition ◽  
Methodological Advance ◽  
Meta Analyses ◽  
Observed Score

Meta-analysis is a significant methodological advance that is increasingly important in research synthesis. Fundamental to meta-analysis is the presumption that effect sizes, such as the standardized mean difference (SMD), based on scores from different measures are comparable. It has been argued that population observed score SMDs based on scores from different measures A and B will be equal only if the conjunction of three conditions are met: construct equivalence (CE), equal reliabilities (ER), and the absence of differential test functioning (DTF) in all subpopulations of the combined populations of interest. It has also been speculated the results of a meta-analysis of SMDs might differ between circumstances in which the SMDs included in a meta-analysis are based on measures which all met the conjunction of these conditions and that in which the conjunction of these conditions is violated. No previous studies have tested this conjecture. This Monte Carlo study investigated this hypothesis. A population of studies comparing one of five hypothetical treatments with a placebo condition was simulated. The SMDs in these simulated studies were based on true scores from six hypothetical measures. The scores from some of these measures met the conjunction of CE, ER, and, the absence of DTF, while others failed to meet CE. Three meta-analyses were conducted using both fixed effects and random effects methods. The results suggested that the results of meta-analyses can vary to a practically significant degree when the SMDs were based on scores from measures failing to meet the CE condition. Implications for future research are considered.

scholarly journals A Meta-analysis of the Relation Between Math Anxiety and Math Achievement

2020 ◽  
Author(s):  
Connie Barroso ◽  
Colleen Marie Ganley ◽  
Amanda McGraw ◽  
Elyssa A Geer ◽  
Sara Ann Hart ◽  
...  
Keyword(s):  
Math Achievement ◽  
Math Anxiety ◽  
Meta Analysis ◽  
Number System ◽  
Effect Sizes ◽  
Future Research ◽  
Statistics Anxiety ◽  
Math Ability ◽  
Negative Effect ◽  
Meta Analyses

Meta-analyses from the 1990s have previously established a significant, small-to-moderate, and negative correlation between math achievement and math anxiety. Since these publications, research has continued to investigate this relation with more diverse samples and measures. Thus, the goal of the present meta-analysis was to provide an update of the math anxiety-math achievement relation and its moderators. Analyzing 747 effect sizes accumulated from research conducted between 1992 and 2018, we found a small-to-moderate, negative, and statistically significant correlation (r = -.28) between math anxiety and math achievement. The relation was significant for all moderator subgroups, with the exception of the relation between math anxiety and assessments measuring the approximate number system. Grade level, math ability level, adolescent/adult math anxiety scales, math topic of anxiety scale, and math assessments were significant moderators of this relation. There is also a tendency for published studies to report significantly stronger correlations than unpublished studies but, overall, large, negative effect sizes are under-reported. Our results are consistent with previous findings of a significant relation between math anxiety and math achievement. This association starts in childhood, remains significant through adulthood, is smaller for students in grades 3 through 5 and postsecondary school, is larger for math anxiety than for statistics anxiety and for certain math anxiety scales, and is smaller for math exam grades and samples selected for low math ability. This work supports future research efforts to determine effective math achievement and math anxiety interventions, which may be most helpful to implement during childhood.

scholarly journals The Relationship between Family Violence and Self-Control in Adolescence: A Multi-Level Meta-Analysis

2018 ◽  
Author(s):  
Yayouk E. Willems ◽  
Jian-bin Li ◽  
Anne M. Hendriks ◽  
Meike Bartels ◽  
Catrin Finkenauer
Keyword(s):  
Family Violence ◽  
Statistical Power ◽  
Meta Analysis ◽  
Self Control ◽  
Effect Sizes ◽  
Future Research ◽  
Cross Sectional ◽  
Multi Level ◽  
Meta Analyses ◽  
Low Self Control

Theoretical studies propose an association between family violence and low self-control in adolescence, yet empirical findings of this association are inconclusive. The aim of the present research was to systematically summarize available findings on the relation between family violence and self-control across adolescence. We included 27 studies with 143 effect sizes, representing more than 25,000 participants of eight countries from early to late adolescence. Applying a multi-level meta-analyses, taking dependency between effect sizes into account while retaining statistical power, we examined the magnitude and direction of the overall effect size. Additionally, we investigated whether theoretical moderators (e.g., age, gender, country), and methodological moderators (cross-sectional/longitudinal, informant) influenced the magnitude of the association between family violence and self-control. Our results revealed that family violence and self-control have a small to moderate significant negative association (r = -.191). This association did not vary across gender, country, and informants. The strength of the association, however, decreased with age and in longitudinal studies. This finding provides evidence that researchers and clinicians may expect low self-control in the wake of family violence, especially in early adolescence. Recommendations for future research in the area are discussed.

scholarly journals The anatomy of an award-winning meta-analysis: Recommendations for authors, reviewers, and readers of meta-analytic reviews

2021 ◽  
Author(s):  
Piers Steel ◽  
Sjoerd Beugelsdijk ◽  
Herman Aguinis
Keyword(s):  
Meta Analysis ◽  
Effect Sizes ◽  
Future Research ◽  
Research Directions ◽  
Outlier Identification ◽  
Business Studies ◽  
Award Winning ◽  
Future Research Directions ◽  
Meta Analyses ◽  
Highly Cited

AbstractMeta-analyses summarize a field’s research base and are therefore highly influential. Despite their value, the standards for an excellent meta-analysis, one that is potentially award-winning, have changed in the last decade. Each step of a meta-analysis is now more formalized, from the identification of relevant articles to coding, moderator analysis, and reporting of results. What was exemplary a decade ago can be somewhat dated today. Using the award-winning meta-analysis by Stahl et al. (Unraveling the effects of cultural diversity in teams: A meta-analysis of research on multicultural work groups. Journal of International Business Studies, 41(4):690–709, 2010) as an exemplar, we adopted a multi-disciplinary approach (e.g., management, psychology, health sciences) to summarize the anatomy (i.e., fundamental components) of a modern meta-analysis, focusing on: (1) data collection (i.e., literature search and screening, coding), (2) data preparation (i.e., treatment of multiple effect sizes, outlier identification and management, publication bias), (3) data analysis (i.e., average effect sizes, heterogeneity of effect sizes, moderator search), and (4) reporting (i.e., transparency and reproducibility, future research directions). In addition, we provide guidelines and a decision-making tree for when even foundational and highly cited meta-analyses should be updated. Based on the latest evidence, we summarize what journal editors and reviewers should expect, authors should provide, and readers (i.e., other researchers, practitioners, and policymakers) should consider about meta-analytic reviews.

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.

Reporting and Reproducibility of Meta-Analysis in Speech, Language, and Hearing Research

2021 ◽  
pp. 1-8
Author(s):  
Jason C. Chow ◽  
Ashlee L. Sjogren ◽  
Hongyang Zhao
Keyword(s):  
Meta Analysis ◽  
Future Research ◽  
Data Sets ◽  
Full Data ◽  
Hearing Research ◽  
The Core ◽  
Meta Review ◽  
Core Elements ◽  
Meta Analyses ◽  
Over Time

Purpose The purposes of this meta-review are to (a) articulate the importance of transparency and reproducibility in meta-analysis, (b) assess the transparency and reproducibility of meta-analyses published in journals of the American Speech-Language-Hearing Association (ASHA), and (c) discuss the implications of our findings and recommendations for future research. Method We conducted a meta-review of all meta-analyses published in ASHA journals through December 31, 2020. Our systematic review yielded 47 meta-analyses for inclusion in this review. We coded all eligible reports on the core elements of transparency and reproducibility in meta-analysis. Results Our findings suggest that though reporting tendencies have improved over time, much work is needed to promote transparency and reproducibility in meta-analytic work. Key areas for future accountability include preregistering study protocol, using Preferred Reporting in Systematic Reviews and Meta-Analysis checklists, providing full data sets, and publishing analytic codes. Conclusions The state of reporting in meta-analysis is improving over time. We conclude with a discussion of specific areas that need further attention, and recommendations for researchers to consider when conducting future meta-analyses. Supplemental Material https://doi.org/10.23641/asha.14888481

Comorbidity of Obsessive-Compulsive and Psychotic Experiences: A systematic review and meta-analysis

2020 ◽  
Author(s):  
Lauren Mawn ◽  
Thomas Campbell ◽  
Charlotte Aynsworth ◽  
Helen Beckwith ◽  
Anna Luce ◽  
...  
Keyword(s):  
Psychotic Disorders ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Future Research ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Current Review ◽  
Pooled Prevalence ◽  
Meta Analyses ◽  
Symptom Criteria

BACKGROUND: Comorbidity between obsessive compulsive disorder (OCD) and psychotic disorders has long been a subject of interest and speculation, with much overlap being reported. The current review seeks to: (1) Investigate the prevalence of co-occurring OCD and psychosis, reporting pooled prevalence rates; and (2) Explore variability in reported rates on the basis of categorical and/or dimensional classifications of OCD and psychosis and (3) explore potential moderators of variability. METHOD: A systematic search was performed of key databases (Embase, PSYCHInfo, MEDLINE, Scopus) from January 1988 to October 2017. Included in the meta-analyses were studies that reported adult (18+) prevalence of comorbid OCD, obsessional compulsive symptoms (OCS) and psychosis-related disorders. RESULTS: 94 articles with 103 effect sizes were extracted. Overall, when using categorical diagnoses the prevalence rate of comorbid OCD and psychotic disorder was 12% (n=155649; k= 81; 95% CI=9-15%). Using diagnostic plus symptom criteria, the prevalence was 24% (n=9563; k = 46, 95% CI=20-28%).CONCLUSION: Given the substantial co-occurrence, it is important that individuals presenting in routine clinical practice are assessed for both disorders. To advance understanding, future research must go beyond comorbidity to explore latent dimensions that may account for their development and/or maintenance (e.g., trauma).

scholarly journals Sex Differences in Trust and Trustworthiness - A Meta-Analysis of the Trust Game and the Gift-Exchange Game

2018 ◽  
Author(s):  
Olmo Van den Akker ◽  
Marcel A. L. M. van Assen ◽  
mark van vugt ◽  
Jelte M. Wicherts
Keyword(s):  
Sex Differences ◽  
Sex Difference ◽  
Meta Analysis ◽  
Gift Exchange ◽  
Effect Sizes ◽  
Trust Game ◽  
Future Research ◽  
Analytic Review ◽  
The Gift ◽  
Meta Analyses

Do men and women differ in trusting behavior? This question is directly relevant to social, economic, and political domains, yet the answer remains elusive. In this paper, we present a meta-analytic review of the literature on sex differences in the trust game and a variant, the gift-exchange game. Informed by both evolutionary and cultural perspectives, we predicted men to be more trusting and women to be more trustworthy in these games. The trust game meta-analyses encompass 77 papers yielding 174 effect sizes based on 17,082 participants from 23 countries, while the gift-exchange game meta-analyses covered 15 papers reporting 35 effect sizes based on 1,362 participants from 19 countries. In the trust game, we found men to be more trusting than women, g = 0.22, but we found no significant sex difference in trustworthiness, g = 0.09. In the gift-exchange game we found no significant sex difference in trust, g = 0.15, yet we did find that men are more trustworthy than women, g = 0.33. The results of the meta-analyses show that the behavior in both games is inconsistent. It seems that when monetary transfers are multiplied men behave more cooperatively than women, but that there are no sex differences when such a multiplier is absent. This “male multiplier effect” is consistent with an evolutionary account emphasizing men’s historical role as resource provider. However, future research needs to substantiate this effect and provide a theoretical framework to explain it.

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews &amp; Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Sign in / Sign up

Export Citation Format

Share Document