Methods for estimating between-study variance and overall effect in meta-analysis of odds-ratios

In random-effects meta-analysis the between-study variance (τ 2) has a key role in assessing heterogeneity of study-level estimates and combining them to estimate an overall effect. For odds ratios the most common methods suffer from bias in estimating τ 2 and the overall effect and produce confidence intervals with below-nominal coverage. An improved approximation to the moments of Cochran's Q statistic, suggested by Kulinskaya and Dollinger (KD), yields new point and interval estimators of τ 2 and of the overall log-odds-ratio. Another, simpler approach (SSW) uses weights based only on study-level sample sizes to estimate the overall effect. In extensive simulations we compare our proposed estimators with established point and interval estimators for τ 2 and point and interval estimators for the overall log-odds-ratio (including the Hartung-Knapp-Sidik-Jonkman interval). Additional simulations included three estimators based on generalized linear mixed models and the Mantel-Haenszel fixed-effect estimator. Results of our simulations show that no single point estimator of τ 2 can be recommended exclusively, but Mandel-Paule and KD provide better choices for small and large numbers of studies, respectively. The KD estimator provides reliable coverage of τ 2. Inverse-variance-weighted estimators of the overall effect are substantially biased, as are the Mantel-Haenszel odds ratio and the estimators from the generalized linear mixed models. The SSW estimator of the overall effect and a related confidence interval provide reliable point and interval estimation of the overall log-odds-ratio

Nutrigenomics 2.0: The Need for Ongoing and Independent Evaluation and Synthesis of Commercial Nutrigenomics Tests' Scientific Knowledge Base for Responsible Innovation

Nutrigenomics is an important strand of precision medicine that examines the bidirectional interactions of the genome and nutritional exposures, and attendant health and disease outcomes. This perspectives article presents the new concept of "Nutrigenomics 2.0," so as to cultivate and catalyze the next generation research and funding priorities for responsible and sustainable knowledge-based innovations. We further contextualize our recent study of the 38 genes included in commercially available nutrigenomics tests, and offer additional context in relation to the 2014 American Academy of Nutrition and Dietetics position. Finally, we make a call in the best interest of the nutrigenomics science community, governments, global society, and commercial nutrigenomics test providers that new evidence evaluation and synthesis platforms are created concerning nutrigenomics tests before they become commercially available. The proposed assessment and synthesis of nutrigenomics data should be carried out on an ongoing dynamic basis with periodic intervals and/or when there is a specific demand for evidence synthesis, and importantly, in ways that are transparent where conflict of interests are disclosed fully by the involved parties, be they scientists, industry, governments, citizens, social scientists, or ethicists. We submit that this will cultivate responsible innovation, and business models that are sustainable, robust, and stand the test of time and context

Introducing EMMIE: An evidence rating scale to encourage mixed-method crime prevention synthesis reviews

Objectives This short report describes the need for, and the development of, a coding system to distil the quality and coverage of systematic reviews of the evidence relating to crime prevention interventions. The starting point for the coding system concerns the evidence needs of policymakers and practitioners. Methods The coding scheme (EMMIE) proposed builds on previous scales that have been developed to assess the probity, coverage and utility of evidence both in health and criminal justice. It also draws on the principles of realist synthesis and review. Results The proposed EMMIE scale identifies five dimensions to which systematic reviews intended to inform crime prevention should speak. These are the Effect of intervention, the identification of the causal Mechanism(s) through which interventions are intended to work, the factors that Moderate their impact, the articulation of practical Implementation issues, and the Economic costs of intervention

From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions

Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic interactions (GIs) in Saccharomyces cerevisiae. The interpretation of these data is often difficult, but it can be improved by the joint analysis of GIs along with complementary data types. Here, we describe a novel methodology that integrates genetic and physical interaction data. We use our method to identify a collection of functional modules related to chromosomal biology and to investigate the relations among them. We show how the resulting map of modules provides clues for the elucidation of function both at the level of individual genes and at the level of functional modules

The role of agri-environment schemes in conservation and environmental management.

Over half of the European landscape is under agricultural management and has been for millennia. Many species and ecosystems of conservation concern in Europe depend on agricultural management and are showing ongoing declines. Agri-environment schemes (AES) are designed partly to address this. They are a major source of nature conservation funding within the European Union (EU) and the highest conservation expenditure in Europe. We reviewed the structure of current AES across Europe. Since a 2003 review questioned the overall effectiveness of AES for biodiversity, there has been a plethora of case studies and meta-analyses examining their effectiveness. Most syntheses demonstrate general increases in farmland biodiversity in response to AES, with the size of the effect depending on the structure and management of the surrounding landscape. This is important in the light of successive EU enlargement and ongoing reforms of AES. We examined the change in effect size over time by merging the data sets of 3 recent meta-analyses and found that schemes implemented after revision of the EU's agri-environmental programs in 2007 were not more effective than schemes implemented before revision. Furthermore, schemes aimed at areas out of production (such as field margins and hedgerows) are more effective at enhancing species richness than those aimed at productive areas (such as arable crops or grasslands). Outstanding research questions include whether AES enhance ecosystem services, whether they are more effective in agriculturally marginal areas than in intensively farmed areas, whether they are more or less cost-effective for farmland biodiversity than protected areas, and how much their effectiveness is influenced by farmer training and advice? The general lesson from the European experience is that AES can be effective for conserving wildlife on farmland, but they are expensive and need to be carefully designed and targeted.This is the final published version. It first appeared from Wiley http://dx.doi.org/10.1111/cobi.1253

Salvage logging effects on regulating ecosystem services and fuel loads

We thank several authors who generously provided data for this meta-analysis (WebPanel 2). ABL acknowledges the support of mobility grants from Universidad de Alcalá and Spanish Ministry of Education, postdoctoral fellowships from the Spanish Ministry of Economy and the Alexander von Humboldt Foundation, and Project AS2013/MAE-2719 “REMEDINAL-3” from the Government of Madrid. The data underlying this paper are available through an institutional repository (http://hdl.handle.net/10481/62260).Salvage logging, or logging after natural disturbances such as wildfires, insect outbreaks, and windstorms, is carried out to recover some of a forest’s natural and/or economic capital. However, trade-offs between management objectives and a lack of consensus on the ecological consequences of salvage logging impair science-based decision making on the management of forests after natural disturbances. We conducted a global meta-analysis of the impacts of salvage logging on regulating ecosystem services and on fuel loads, as a frequent post-disturbance objective is preventing subsequent wildfires that could be fueled by the accumulation of dead trunks and branches. Salvage logging affected ecosystem services in a moderately negative way, regardless of disturbance type and severity, time elapsed since salvage logging, intensity of salvage logging, and the group of regulating ecosystem services being considered. However, prolonging the time between natural disturbance and salvage logging mitigated negative effects on regulating ecosystem services. Salvage logging had no overall effect on surface fuels; rather, different fuel types responded differently depending on the time elapsed since salvage logging. Delaying salvage logging by ~2–4 years may reduce negative ecological impacts without affecting surface fuel loads.Project AS2013/MAE-2719 “REMEDINAL-3” from the Government of Madri

Gauging the Effectiveness of Educational Technology Integration in Education: What the Best-Quality Meta-Analyses Tell Us

This chapter examines quantitative research in the literature of technology integration in education from the perspective of the meta-analyses of primary studies conducted from 1982 to 2015. The intent is to identify and review the best of these meta-analyses. Fifty-two meta-analyses were originally identified and evaluated for methodological quality using the Meta-Analysis Methodological Quality Review Guide (MMQRG), and the best 20 were selected and are included for review here. Some describe the effects of technology integration within specific content areas and some are more general. Technology integration in education is one of the most fluid areas of research, reflecting the incredible pace of the evolution of computer-based tools and applications. Just navigating through the vast primary empirical literature presents a real challenge to those interested in evaluating the educational effectiveness of technology. Systematic reviews in the field are numerous and quite diverse in their methodological quality, introducing potential bias in the interpretation of findings (Bernard RM, Borokhovski E, Schmid RF, Tamim RM. J Comput High Educ 26(3):183–209, 2014), thus bringing into question their applied value. This chapter identifies and reviews the best of these meta-analyses. In addition to overall statistical analyses of this collection, the findings of six of the most recent and best meta-analyses (after 2010) are summarized in more detail. The discussion focuses on the interpretation of the current findings, considers future alternatives to primary research in this area, and examines how meta-analysts might address them