Meta-analysis of Results from Multisite Studies

2013 ◽  
Author(s):  
Jessica Gurevitch
Keyword(s):  
Experimental Work ◽  
Research Group ◽  
Quantitative Research ◽  
Meta Analysis ◽  
Research Question ◽  
Research Synthesis ◽  
Large Group ◽  
Literature Reviews ◽  
Analysis Of Results

Research synthesis in ecology has typically been based on literature reviews, as is also common in other fields. That is, a search is conducted for relevant data addressing a particular research question, the utility of published and unpublished data is assessed, and the results are synthesized to address questions based on all of the available evidence. This chapter discusses the case of individual researchers who wish to combine the results of distinct experiments that they have conducted themselves or within a single research group, sometimes over the course of many years. Such efforts have many similarities with literature-based quantitative research synthesis, but differ in some important ways. It begins with several examples of such work, and investigates the challenges, potential pitfalls, advantages, and issues involved in using meta-analysis for the synthesis of such large-group collaborative experimental work.

scholarly journals Adopting a Meta-Generative Way of Thinking in the Field of Education via the Use of Bayesian Methods: A Multimethod Approach in a Post-Truth and COVID-19 Era1

2020 ◽  
pp. 4-19 ◽  
Author(s):  
Prathiba Natesan Batley ◽  
Peter Boedeker ◽  
Anthony J. Onwuegbuzie
Keyword(s):  
Bayesian Methods ◽  
Null Hypothesis ◽  
Quantitative Research ◽  
Meta Analysis ◽  
Research Synthesis ◽  
Research Data ◽  
Policy Implications ◽  
Significance Testing ◽  
Null Hypothesis Significance Testing ◽  
Multimethod Approach

In this editorial, we introduce the multimethod concept of thinking meta-generatively, which we define as directly integrating findings from the extant literature during the data collection, analysis, and interpretation phases of primary studies. We demonstrate that meta-generative thinking goes further than do other research synthesis techniques (e.g., meta-analysis) because it involves meta-synthesis not only across studies but also within studies—thereby representing a multimethod approach. We describe how meta-generative thinking can be maximized/optimized with respect to quantitative research data/findings via the use of Bayesian methodology that has been shown to be superior to the inherently flawed null hypothesis significance testing. We contend that Bayesian meta-generative thinking is essential, given the potential for divisiveness and far-reaching sociopolitical, educational, and health policy implications of findings that lack generativity in a post-truth and COVID-19 era.

Consensus Among Experts and Research Synthesis: A Comparison of Methods

1998 ◽  
Vol 14 (1) ◽  
pp. 109-122 ◽  
Author(s):  
Paul M. Wortman ◽  
Joshua M. Smyth ◽  
John C. Langenbrunner ◽  
William H. Yeaton
Keyword(s):  
Quantitative Research ◽  
Large Scale ◽  
Scientific Literature ◽  
Research Synthesis ◽  
Consensus Method ◽  
Comparison Of Methods ◽  
High Quality ◽  
Asymptomatic Patients ◽  
Number Of Factors ◽  
Literature Reviews

AbstractA comparison of two assessment methods, consensus among experts and research synthesis of the scientific literature, was performed using a surgical procedure, carotid endarterectomy (CE), as an example. These two methods have been widely advocated as being scientifically valid. While the comparison revealed a number of areas of general agreement, important differences between the two methods emerged. For example, 30-day mortality for asymptomatic patients was considered an effective outcome (ranked first) by the synthesis, but only “quivocal” (ranked third) of six major indicators reported by the consensus method. The synthesis results are also consistent with other literature reviews as well as with recent large-scale randomized trial results. A number of factors that could account for differences between the two methods were examined. Overall, use of consensus panels may be appropriate early in the development of an intervention where the evidence is sparse, while quantitative research synthesis is preferable when a number of high-quality studies have been performed.

Informing Healthy Transport Policies

2005 ◽  
Vol 1908 (1) ◽  
pp. 214-220
Author(s):  
Matt Egan ◽  
Mark Petticrew ◽  
David Ogilvie
Keyword(s):  
Systematic Reviews ◽  
Important Determinant ◽  
Meta Analysis ◽  
Complex Interventions ◽  
Research Synthesis ◽  
Health Impact ◽  
Modal Shift ◽  
Analysis Techniques ◽  
Literature Reviews ◽  
Inform Decision Making

Transport is an important determinant of health, and the health impact of transport interventions requires robust evaluation. Systematic reviews provide a rigorous tool for locating, appraising, and synthesizing evaluative evidence. Some systematic reviews use meta-analysis techniques to synthesize data, but other systematic reviews do not. This paper addresses some methodological and practical issues associated with conducting systematic reviews on the health impact of transport interventions. By using as case studies recently conducted reviews on topics such as the health impact of new roads and the effectiveness of interventions in promoting modal shift, the paper outlines many of the challenges faced by systematic reviewers in this field. It then describes some research synthesis techniques available to systematic reviewers and discusses some of the strengths and weaknesses of these techniques. Systematic literature reviews on the health impact of specific transport interventions can be used to inform decision making. However, reviews of such complex interventions require an innovative approach to the methodologies of systematic reviews and research synthesis.

scholarly journals Using collaboration networks to identify authorship bias in meta-analyses

2019 ◽  
Author(s):  
Thiago C. Moulin ◽  
Olavo B. Amaral
Keyword(s):  
Effect Size ◽  
Research Group ◽  
Meta Analysis ◽  
Research Question ◽  
Collaboration Networks ◽  
Research Groups ◽  
Bias Effect ◽  
Random Effects Models ◽  
Methodological Choices ◽  
Meta Analyses

AbstractMeta-analytic methods are powerful resources to summarize the existing evidence concerning a given research question, and are widely used in many academic fields. However, meta-analyses can be vulnerable to various sources of bias, which should be considered to avoid inaccuracies. Many of these sources can be related to study authorship, as both methodological choices and researcher bias may lead to deviations in results between different research groups. In this work, we describe a method to objectively attribute study authorship within a given meta-analysis to different research groups by using graph cluster analysis of collaboration networks. We then provide empirical examples of how the research group of origin can impact effect size in distinct types of meta-analyses, demonstrating how non-independence between within-group results can bias effect size estimates if uncorrected. Finally, we show that multilevel random-effects models using research group as a level of analysis can be a simple tool for correcting biases related to study authorship.

An Epistemological Criticism of Social Entrepreneurship: Is Social Entrepreneurship a Sound Scientific Field of Research

2018 ◽  
Author(s):  
Amir Forouharfar
Keyword(s):  
Social Entrepreneurship ◽  
Social Constructivism ◽  
Social Epistemology ◽  
American English ◽  
Meta Analysis ◽  
Research Question ◽  
Knowledge Structure ◽  
Scientific Field ◽  
The Other ◽  
First Time

The paper was shaped around the pivotal question: Is SE a sound and scientific field of research? The question has given a critical tone to the paper and has also helped to bring out some of the controversial debates in the realm of SE. The paper was organized under five main discussions to be able to provide a scientific answer to the research question: (1)<b> </b>is “social entrepreneurship” an oxymoron?, (2) the characteristics of SE knowledge, (3) sources of social entrepreneurship knowledge, (4) SE knowledge: structure and limitations and (5) contributing epistemology-making concepts for SE.<b> </b>Based on the sections,<b> </b>the study relied on the relevant philosophical schools of thought in <i>Epistemology </i>(e.g. <i>Empiricism</i>, <i>Rationalism</i>, <i>Skepticism</i>, <i>Internalism</i> vs. <i>Externalism</i>,<i> Essentialism, Social Constructivism</i>, <i>Social Epistemology, etc.</i>) to discuss these controversies around SE and proposes some solutions by reviewing SE literature. Also, to determine the governing linguistic discourse in the realm of SE, which was necessary for our discussion,<i> Corpus of Contemporary American English (COCA)</i> for the first time in SE studies was used. Further, through the study, SE buzzwords which constitute SE terminology were derived and introduced to help us narrowing down and converging the thoughts in this field and demarking the epistemological boundaries of SE. The originality of the paper on one hand lies in its pioneering discussions on SE epistemology and on the other hand in paving the way for a construction of sound epistemology for SE; therefore in many cases after preparing the philosophical ground for the discussions, it went beyond the prevalent SE literature through meta-analysis to discuss the cases which were raised. The results of the study verified previously claimed embryonic pre-paradigmatic phase in SE which was far from a sound and scientific knowledge, although the scholarly endeavors are the harbingers of such a possibility in the future which calls for further mature academic discussion and development of SE knowledge by the SE academia.

scholarly journals Application of the Subspace-Based Methods in Health Monitoring of Civil Structures: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 10 (10) ◽  
pp. 3607
Author(s):  
Hoofar Shokravi ◽  
Hooman Shokravi ◽  
Norhisham Bakhary ◽  
Mahshid Heidarrezaei ◽  
Seyed Saeid Rahimian Koloor ◽  
...  
Keyword(s):  
System Identification ◽  
Systematic Reviews ◽  
Health Monitoring ◽  
Meta Analysis ◽  
Civil Structures ◽  
Literature Reviews ◽  
Research Gap ◽  
Meta Analyses ◽  
Subspace System Identification ◽  
Insight Into

A large number of research studies in structural health monitoring (SHM) have presented, extended, and used subspace system identification. However, there is a lack of research on systematic literature reviews and surveys of studies in this field. Therefore, the current study is undertaken to systematically review the literature published on the development and application of subspace system identification methods. In this regard, major databases in SHM, including Scopus, Google Scholar, and Web of Science, have been selected and preferred reporting items for systematic reviews and meta-analyses (PRISMA) has been applied to ensure complete and transparent reporting of systematic reviews. Along this line, the presented review addresses the available studies that employed subspace-based techniques in the vibration-based damage detection (VDD) of civil structures. The selected papers in this review were categorized into authors, publication year, name of journal, applied techniques, research objectives, research gap, proposed solutions and models, and findings. This study can assist practitioners and academicians for better condition assessment of structures and to gain insight into the literature.

scholarly journals Prognostic factors for chronic post-surgical pain after lung or pleural surgery: a protocol for a systematic review and meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e051554
Author(s):  
Pascal Richard David Clephas ◽  
Sanne Elisabeth Hoeks ◽  
Marialena Trivella ◽  
Christian S Guay ◽  
Preet Mohinder Singh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Prognostic Factors ◽  
Prognostic Factor ◽  
Meta Analysis ◽  
Case Series ◽  
Related Factors ◽  
Surgical Pain ◽  
Literature Reviews ◽  
Chronic Post Surgical Pain

IntroductionChronic post-surgical pain (CPSP) after lung or pleural surgery is a common complication and associated with a decrease in quality of life, long-term use of pain medication and substantial economic costs. An abundant number of primary prognostic factor studies are published each year, but findings are often inconsistent, methods heterogeneous and the methodological quality questionable. Systematic reviews and meta-analyses are therefore needed to summarise the evidence.Methods and analysisThe reporting of this protocol adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) checklist. We will include retrospective and prospective studies with a follow-up of at least 3 months reporting patient-related factors and surgery-related factors for any adult population. Randomised controlled trials will be included if they report on prognostic factors for CPSP after lung or pleural surgery. We will exclude case series, case reports, literature reviews, studies that do not report results for lung or pleural surgery separately and studies that modified the treatment or prognostic factor based on pain during the observation period. MEDLINE, Scopus, Web of Science, Embase, Cochrane, CINAHL, Google Scholar and relevant literature reviews will be searched. Independent pairs of two reviewers will assess studies in two stages based on the PICOTS criteria. We will use the Quality in Prognostic Studies tool for the quality assessment and the CHARMS-PF checklist for the data extraction of the included studies. The analyses will all be conducted separately for each identified prognostic factor. We will analyse adjusted and unadjusted estimated measures separately. When possible, evidence will be summarised with a meta-analysis and otherwise narratively. We will quantify heterogeneity by calculating the Q and I2 statistics. The heterogeneity will be further explored with meta-regression and subgroup analyses based on clinical knowledge. The quality of the evidence obtained will be evaluated according to the Grades of Recommendation Assessment, Development and Evaluation guideline 28.Ethics and disseminationEthical approval will not be necessary, as all data are already in the public domain. Results will be published in a peer-reviewed scientific journal.PROSPERO registration numberCRD42021227888.

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