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JournalISSN: 1759-2879

Research Synthesis Methods 

Wiley-Blackwell
About: Research Synthesis Methods is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Systematic review & Medicine. It has an ISSN identifier of 1759-2879. Over the lifetime, 590 publications have been published receiving 34025 citations.


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TL;DR: This paper explains the key assumptions of each model, and outlines the differences between the models, to conclude with a discussion of factors to consider when choosing between the two models.
Abstract: There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright © 2010 John Wiley & Sons, Ltd.

3,883 citations

Journal ArticleDOI
TL;DR: The purpose of this scoping review was to provide an overview of scoping reviews in the literature.
Abstract: Background The scoping review has become an increasingly popular approach for synthesizing research evidence. It is a relatively new approach for which a universal study definition or definitive procedure has not been established. The purpose of this scoping review was to provide an overview of scoping reviews in the literature. Methods A scoping review was conducted using the Arksey and O'Malley framework. A search was conducted in four bibliographic databases and the gray literature to identify scoping review studies. Review selection and characterization were performed by two independent reviewers using pretested forms. Results The search identified 344 scoping reviews published from 1999 to October 2012. The reviews varied in terms of purpose, methodology, and detail of reporting. Nearly three-quarter of reviews (74.1%) addressed a health topic. Study completion times varied from 2 weeks to 20 months, and 51% utilized a published methodological framework. Quality assessment of included studies was infrequently performed (22.38%). Conclusions Scoping reviews are a relatively new but increasingly common approach for mapping broad topics. Because of variability in their conduct, there is a need for their methodological standardization to ensure the utility and strength of evidence. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

1,695 citations

Journal ArticleDOI
TL;DR: Standard diagnostic procedures developed for linear regression analyses are extended to the meta-analytic fixed- and random/mixed-effects models to illustrate the usefulness of these procedures in various research settings.
Abstract: The presence of outliers and influential cases may affect the validity and robustness of the conclusions from a meta-analysis. While researchers generally agree that it is necessary to examine outlier and influential case diagnostics when conducting a meta-analysis, limited studies have addressed how to obtain such diagnostic measures in the context of a meta-analysis. The present paper extends standard diagnostic procedures developed for linear regression analyses to the meta-analytic fixed- and random/mixed-effects models. Three examples are used to illustrate the usefulness of these procedures in various research settings. Issues related to these diagnostic procedures in meta-analysis are also discussed. Copyright © 2010 John Wiley & Sons, Ltd.

1,335 citations

Journal ArticleDOI
TL;DR: A new tool, robvis (Risk‐Of‐Bias VISualization), is presented, available as an R package and web app, which facilitates rapid production of publication‐quality risk‐of‐bias assessment figures.
Abstract: Despite a major increase in the range and number of software offerings now available to help researchers produce evidence syntheses, there is currently no generic tool for producing figures to display and explore the risk-of-bias assessments that routinely take place as part of systematic review. However, tools such as the R programming environment and Shiny (an R package for building interactive web apps) have made it straightforward to produce new tools to help in producing evidence syntheses. We present a new tool, robvis (Risk-Of-Bias VISualization), available as an R package and web app, which facilitates rapid production of publication-quality risk-of-bias assessment figures. We present a timeline of the tool's development and its key functionality.

1,297 citations

Journal ArticleDOI
TL;DR: This paper provides an estimator of the covariance matrix of meta-regression coefficients that is applicable when there are clusters of internally correlated estimates and demonstrates that the meta- Regression coefficients are consistent and asymptotically normally distributed and that the robust variance estimator is valid even when the covariates are random.
Abstract: Conventional meta-analytic techniques rely on the assumption that effect size estimates from different studies are independent and have sampling distributions with known conditional variances. The independence assumption is violated when studies produce several estimates based on the same individuals or there are clusters of studies that are not independent (such as those carried out by the same investigator or laboratory). This paper provides an estimator of the covariance matrix of meta-regression coefficients that are applicable when there are clusters of internally correlated estimates. It makes no assumptions about the specific form of the sampling distributions of the effect sizes, nor does it require knowledge of the covariance structure of the dependent estimates. Moreover, this paper demonstrates that the meta-regression coefficients are consistent and asymptotically normally distributed and that the robust variance estimator is valid even when the covariates are random. The theory is asymptotic in the number of studies, but simulations suggest that the theory may yield accurate results with as few as 20-40 studies. Copyright © 2010 John Wiley & Sons, Ltd.

1,261 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202333
202283
202187
202066
201943
201848