The Value of Statistical Life: A Meta-analysis of Meta-analyses

Value of Statistical Life (VSL) is one of the most debatable areas in economics. However, VSL is frequently used as a policy instrument for evaluating various safety, health and environmental regulations. Policymakers have to undertake the difficult task of assigning monetary value to the reduction of various health and mortality risks while analyzing safety policies. Compensating wage differential (CWD) for job risks acts as a reference point for valuing mortality risks while VSL serves as a basis to analyze these benefits of risk reduction policies. However, it has been observed in the recent past that VSL estimates vary substantially across various studies. Therefore, it has become necessary for researchers and policymakers to understand the source of this variation in order to aid policymaking. This paper attempts to bring together some of the emerging issues in VSL literature and presents a meta-analysis that is based on 34 observations from 30 hedonic wage-based VSL studies. The results of this meta-analysis show that certain emerging areas in VSL literature such as worker’s compensation benefits, age and long-term health-related job risk require more emphasis and further examination.

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The value of statistical life in road safety: a meta-analysis

Accident Analysis & Prevention ◽

10.1016/s0001-4575(02)00105-7 ◽

2003 ◽

Vol 35 (6) ◽

pp. 973-986 ◽

Cited By ~ 154

Author(s):

Arianne de Blaeij ◽

Raymond J.G.M Florax ◽

Piet Rietveld ◽

Erik Verhoef

Keyword(s):

Road Safety ◽

Meta Analysis ◽

Value Of Statistical Life ◽

Statistical Life

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A Meta-Analysis of Interviews and Cognitive Ability

Journal of Personnel Psychology ◽

10.1027/1866-5888/a000091 ◽

2013 ◽

Vol 12 (4) ◽

pp. 157-169 ◽

Cited By ~ 7

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.

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Power-Enhanced Funnel Plots for Meta-Analysis

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000392 ◽

2020 ◽

Vol 228 (1) ◽

pp. 43-49 ◽

Cited By ~ 1

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.

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Which Data to Meta-Analyze, and How?

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000357 ◽

2019 ◽

Vol 227 (1) ◽

pp. 64-82 ◽

Cited By ~ 3

Author(s):

Martin Voracek ◽

Michael Kossmeier ◽

Ulrich S. Tran

Keyword(s):

Empirical Research ◽

Meta Analysis ◽

Curve Analysis ◽

Research Progress ◽

Primary Data ◽

Statistical Procedures ◽

Graphical Displays ◽

Primary Data Analysis ◽

Meta Analyses ◽

Data Analytic

Abstract. Which data to analyze, and how, are fundamental questions of all empirical research. As there are always numerous flexibilities in data-analytic decisions (a “garden of forking paths”), this poses perennial problems to all empirical research. Specification-curve analysis and multiverse analysis have recently been proposed as solutions to these issues. Building on the structural analogies between primary data analysis and meta-analysis, we transform and adapt these approaches to the meta-analytic level, in tandem with combinatorial meta-analysis. We explain the rationale of this idea, suggest descriptive and inferential statistical procedures, as well as graphical displays, provide code for meta-analytic practitioners to generate and use these, and present a fully worked real example from digit ratio (2D:4D) research, totaling 1,592 meta-analytic specifications. Specification-curve and multiverse meta-analysis holds promise to resolve conflicting meta-analyses, contested evidence, controversial empirical literatures, and polarized research, and to mitigate the associated detrimental effects of these phenomena on research progress.

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

10.32942/osf.io/epqa7 ◽

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.

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Laser Influence on Dental Sensitivity Compared to Other Light Sources Used During In-office Dental Bleaching: Systematic Review and Meta-analysis

Operative Dentistry ◽

10.2341/19-064-l ◽

2020 ◽

Vol 45 (6) ◽

pp. 589-597

Author(s):

BGS Casado ◽

EP Pellizzer ◽

JR Souto Maior ◽

CAA Lemos ◽

BCE Vasconcelos ◽

...

Keyword(s):

Randomized Clinical Trials ◽

Color Change ◽

Meta Analysis ◽

Present Review ◽

Cochrane Library ◽

Light Sources ◽

Eligibility Criteria ◽

Tooth Color ◽

Significant Difference ◽

Meta Analyses

Clinical Relevance The use of laser light during bleaching will not reduce the incidence or severity of sensitivity and will not increase the degree of color change compared with nonlaser light sources. SUMMARY Objective: To evaluate whether the use of laser during in-office bleaching promotes a reduction in dental sensitivity after bleaching compared with other light sources. Methods: The present review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and is registered with PROSPERO (CDR42018096591). Searches were conducted in the PubMed/Medline, Web of Science, and Cochrane Library databases for relevant articles published up to August 2018. Only randomized clinical trials among adults that compared the use of laser during in-office whitening and other light sources were considered eligible. Results: After analysis of the texts retrieved during the database search, six articles met the eligibility criteria and were selected for the present review. For the outcome dental sensitivity, no significant difference was found favoring any type of light either for intensity (mean difference [MD]: −1.60; confidence interval [CI]: −3.42 to 0.22; p=0.09) or incidence (MD: 1.00; CI: 0.755 to 1.33; p=1.00). Regarding change in tooth color, no significant differences were found between the use of the laser and other light sources (MD: −2.22; CI: −6.36 to 1.93; p=0.29). Conclusions: Within the limitations of the present study, laser exerts no influence on tooth sensitivity compared with other light sources when used during in-office bleaching. The included studies demonstrated that laser use during in-office bleaching may have no influence on tooth color change.

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Identification of and Correction for Publication Bias: Comment

10.31222/osf.io/dh87m ◽

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 & 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%.

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