scholarly journals Fostering Scientific Meta-analyses with Knowledge Graphs: A Case-Study

2020 ◽  
pp. 287-303
Author(s):  
Ilaria Tiddi ◽  
Daniel Balliet ◽  
Annette ten Teije
Keyword(s):  
Knowledge Graphs ◽  
Meta Analyses

Network vs. Pairwise Meta-Analyses: A Case Study of the Impact of an Evidence-Synthesis Paradigm on Value of Information Outcomes

2014 ◽  
Vol 32 (10) ◽  
pp. 995-1004 ◽  
Author(s):  
Zafar Zafari ◽  
Kristian Thorlund ◽  
J. Mark FitzGerald ◽  
Carlo A. Marra ◽  
Mohsen Sadatsafavi
Keyword(s):  
Value Of Information ◽  
Evidence Synthesis ◽  
Meta Analyses ◽  
The Impact

scholarly journals Sustainability and Resilience of Emerging Cities in Times of COVID-19

2021 ◽  
Vol 13 (16) ◽  
pp. 9480
Author(s):  
Angela Ivette Grijalba Castro ◽  
Leonardo Juan Ramírez López
Keyword(s):  
Urban Planning ◽  
Natural Resources ◽  
Main Argument ◽  
State Of Emergency ◽  
Ecological Footprints ◽  
Scientific Papers ◽  
Considerable Impact ◽  
New Challenges ◽  
Meta Analyses

The organization of a territory relies on a group of transformations produced by economic, environmental, and social emergencies, generating disruptions along with history. Furthermore, every new scenario generates a considerable impact, which makes it more difficult to recover from increasing urban ecological footprints. COVID-19-emergence-aware cities face new challenges that will test their resilience. This new outline constitutes a study regarding urban planning from an environmental and resilience perspective within this new pandemic state of emergency. It contains four main topics: emergent cities, natural resources, sustainability, and resilience. The document shows a case study carried out in a Colombian town named Cajicá, where a bibliometric inquiry conducted with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) adjustments was managed, tested on forty-one scientific papers; all the above were verified by VOSviewer software tools. The study reveals the creation and visualization of several keyword networks and relations retrieved from all the selected articles, along with the use of eight additional documents for all relation analyses. Sustainability and resilience are the main findings, supported as a process of functionality within urban planning. Sustainability findings’ results are prioritized, along with resilience analysis processes, which are both frameworks used during the COVID-19 pandemic; they constitute the main argument within this set of changes, building on alterations of lifestyle and behavioral situations within the main cities.

A Simple, Principled Approach to Combining Evidence From Meta-Analysis and High-Quality Replications

2018 ◽  
Vol 1 (2) ◽  
pp. 174-185 ◽  
Author(s):  
Evan C. Carter ◽  
Michael E. McCullough
Keyword(s):  
Meta Analysis ◽  
Ego Depletion ◽  
Practical Significance ◽  
High Quality ◽  
Questionable Research Practices ◽  
Combining Evidence ◽  
Meta Analyses ◽  
Work Done ◽  
Combining Information

Recent discussions of the influence of publication bias and questionable research practices on psychological science have increased researchers’ interest in both bias-correcting meta-analytic techniques and preregistered replication. Both approaches have their strengths: For example, meta-analyses can quantitatively characterize the full body of work done in the field of interest, and preregistered replications can be immune to bias. Both approaches also have clear weaknesses: Decisions about which meta-analytic estimates to interpret tend to be controversial, and replications can be discounted for failing to address important methodological heterogeneity. Using the experimental literature on ego depletion as a case study, we illustrate a principled approach to combining information from meta-analysis with information from subsequently conducted high-quality replications. This approach (a) compels researchers to explicate their beliefs in meta-analytic conclusions (and also, when controversy arises, to defend the basis for those beliefs), (b) encourages consideration of practical significance, and (c) facilitates the process of planning replications by specifying the sample sizes necessary to have a reasonable chance of changing the minds of other researchers.

scholarly journals Using Systematic Reviews and Meta-Analyses to Support Regulatory Decision Making for Neurotoxicants: Lessons Learned from a Case Study of PCBs

2010 ◽  
Vol 118 (6) ◽  
pp. 727-734 ◽  
Author(s):  
Michael Goodman ◽  
Katherine Squibb ◽  
Eric Youngstrom ◽  
Laura Gutermuth Anthony ◽  
Lauren Kenworthy ◽  
...  
Keyword(s):  
Decision Making ◽  
Systematic Reviews ◽  
Lessons Learned ◽  
Regulatory Decision ◽  
Meta Analyses

scholarly journals 919Step-by-step guidance on prospective meta-analyses

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Anna Lene Seidler ◽  
Kylie Hunter ◽  
Saskia Cheyne ◽  
Jesse Berlin ◽  
Davina Ghersi ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Meta Analysis ◽  
Analysis Committee ◽  
Medical Databases ◽  
Expert Opinions ◽  
Use Of Data ◽  
Recent Case Study ◽  
Technical Advances ◽  
Meta Analyses

Abstract Focus of Presentation In a prospective meta-analysis (PMA), studies are included before their results are known. This can reduce risk of publication bias and selective outcome reporting, and enables researchers to harmonise their research efforts. Despite rising numbers, there is little guidance on how to conduct PMA. We, the Cochrane PMA Methods Group, developed step-by-step guidance based on a scoping review, and expert opinions and experiences. Each step is illustrated with a recent case study. Findings We describe seven steps for conducting PMA. After developing a protocol (Steps 1), a systematic search for eligible planned/ongoing studies should be conducted, including a search of registries, medical databases and contacting stakeholders (Step 2-3). These studies are then invited to form a collaboration (Step 4), ideally including a steering and data analysis committee. Next, important study features such as common core outcomes and confounders are agreed upon (Step 5). This reduces heterogeneity and increases the number of available outcomes for meta-analysis. Certainty of evidence is assessed by adapting tools such as GRADE (Step 6). Results should be reported using adapted versions of reporting tools such as PRISMA (Step 7). Conclusions/Implications PMA reduce many problems of traditional retrospective systematic reviews and meta-analysis. Updated guidance and recent technical advances will help increase their numbers further. Key messages PMA are ‘next generation systematic reviews’ that allow for greatly improved use of data, whilst reducing bias and research waste. This step-by-step guidance will enable more researchers to conduct successful PMA.

Statistical Models for the Meta-analysis of Nonindependent Data

2013 ◽  
Author(s):  
Kerrie Mengersen ◽  
Michael D. Jennions ◽  
Christopher H. Schmid
Keyword(s):  
Statistical Models ◽  
Single Case ◽  
Meta Analysis ◽  
Dry Weight ◽  
Multiple Treatments ◽  
The Individual ◽  
Meta Analyses ◽  
Size Estimates ◽  
Over Time

In many meta-analyses, independence is questionable because there are several effect estimates per study and/or some of the individual studies included in the meta-analysis might not provide independent estimates of the effect. Within-study nonindependence can arise due to multiple measures of the same effect on the same experimental units being made over time, multiple treatments being compared to the same set of control individuals, or different measures being taken (e.g., plant height, dry weight, and photosynthesis rate) from the same experimental units to generate several different effect size estimates. This chapter discusses nonindependence among effect sizes both within and among studies. It focuses on four commonplace situations where nonindependence can occur in ecology and evolution meta-analyses. Each of these four situations is illustrated with a single case study.

The Assessment of Cognitive Dysfunction in Major Depressive Disorder

2019 ◽  
pp. 59-72
Author(s):  
John E. Harrison
Keyword(s):  
Depressive Disorders ◽  
Cognitive Status ◽  
Development Programme ◽  
Major Depressive ◽  
Recent Case Study ◽  
Technological Developments ◽  
Major Depressive Disorders ◽  
Meta Analyses

Accurately capturing an individual’s cognitive status is a key requirement for identifying levels of impairment in patients with central nervous system indications, including in those with diagnoses of major depressive disorders (MDD). This requirement extends to the determination of whether a therapeutic intervention has impacted cognition and, if so, the extent to which this has occurred. In this chapter we will consider these issues with respect to the assessment of cognition in patients with MDD. We begin with a review of performance on measures reported in recent meta-analyses and with a particular focus on their sensitivity to treatment effects. We proceed to a consideration of how best we might accurately capture levels of cognitive performance and the precautions required to reduce sources of measurement error. These methods will then be considered in the context of a recent case study of a treatment (vortioxetine) development programme. The issues explored in the context of assessing cognition in the vortioxetine programme are then considered in the context of screening for deficits in patients with MDD. We close the chapter with a summary and recommendations for the accurate assessment of cognition, as well as a brief consideration of how technological developments might aid this process.

scholarly journals Analysis of decisions made in meta-analyses of depression screening and the risk of confirmation bias: A case study

2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Felicity A Goodyear-Smith ◽  
Mieke L van Driel ◽  
Bruce Arroll ◽  
Chris Del Mar
Keyword(s):  
Confirmation Bias ◽  
Depression Screening ◽  
Meta Analyses ◽  
Made In

scholarly journals Discovering alignment relations with Graph Convolutional Networks: A biomedical case study

Semantic Web ◽  
2021 ◽  
pp. 1-20
Author(s):  
Pierre Monnin ◽  
Chedy Raïssi ◽  
Amedeo Napoli ◽  
Adrien Coulet
Keyword(s):  
Domain Knowledge ◽  
Knowledge Graph ◽  
Convolutional Networks ◽  
Real World Application ◽  
Web Of Data ◽  
Knowledge Graphs ◽  
The Web ◽  
Node Embeddings ◽  
Weak Similarity

Knowledge graphs are freely aggregated, published, and edited in the Web of data, and thus may overlap. Hence, a key task resides in aligning (or matching) their content. This task encompasses the identification, within an aggregated knowledge graph, of nodes that are equivalent, more specific, or weakly related. In this article, we propose to match nodes within a knowledge graph by (i) learning node embeddings with Graph Convolutional Networks such that similar nodes have low distances in the embedding space, and (ii) clustering nodes based on their embeddings, in order to suggest alignment relations between nodes of a same cluster. We conducted experiments with this approach on the real world application of aligning knowledge in the field of pharmacogenomics, which motivated our study. We particularly investigated the interplay between domain knowledge and GCN models with the two following focuses. First, we applied inference rules associated with domain knowledge, independently or combined, before learning node embeddings, and we measured the improvements in matching results. Second, while our GCN model is agnostic to the exact alignment relations (e.g., equivalence, weak similarity), we observed that distances in the embedding space are coherent with the “strength” of these different relations (e.g., smaller distances for equivalences), letting us considering clustering and distances in the embedding space as a means to suggest alignment relations in our case study.

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