Getting started with meta-analysis (original) (raw)
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Meta-Analysis in a Nutshell: Techniques and General Findings
Economics: The Open-Access, Open-Assessment E-Journal, 2015
The purpose of this article is to introduce the technique and main findings of meta-analysis to the reader, who is unfamiliar with the field and has the usual objections. A meta-analysis is a quantitative survey of a literature reporting estimates of the same parameter. The funnel showing the distribution of the estimates is normally amazingly wide given their t-ratios. Little of the variation can be explained by the quality of the journal (as measured by its impact factor) or by the estimator used. The funnel has often asymmetries consistent with the most likely priors of the researchers, giving a publication bias.
Methodological issues and advances in biological meta-analysis
Evolutionary Ecology, 2012
Meta-analysis has changed the way researchers conduct literature reviews not only in medical and social sciences but also in biological sciences. Meta-analysis in biological sciences, especially in ecology and evolution (which we refer to as 'biological' meta-analysis) faces somewhat different methodological problems from its counterparts in medical and social sciences, where meta-analytic techniques were originally developed. The main reason for such differences is that biological meta-analysis often integrates complex data composed of multiple strata with, for example, different measurements and a variety of species. Here, we review methodological issues and advancements in biological meta-analysis, focusing on three topics: (1) non-independence arising from multiple effect sizes obtained in single studies and from phylogenetic relatedness, (2) detecting and accounting for heterogeneity, and (3) identifying publication bias and measuring its impact. We show how the marriage between mixed-effects (hierarchical/multilevel) models and phylogenetic comparative methods has resolved most of the issues under discussion. Furthermore, we introduce the concept of across-study and within-study metaanalysis, and propose how the use of within-study meta-analysis can improve many empirical studies typical of ecology and evolution.
Meta-analysis: synthesizing research findings in ecology and evolution
Trends in Ecology & Evolution, 1995
C omparisons of sets of studies are at the heart of science: any single study is worth little if not compared and related to other similar studies. In virtually all fields of science, specific hypotheses have been addressed in multiple studies. Furthermore, studies very rarely show identical results, but instead typically differ both in the magnitude of effects and in the occurrence of significant results. Though the heuristic value of reviews and the level at which to make generalizations may be debated', research reviews provide the basis for conceptual syntheses and for develop ment of general theory, and are therefore essential to scientific development. By tradition, reviews in ecology and evolution typically follow a narrative style, and the valid quantitative methods available for summaries of research domains have only recently gained attention. Narrative reviews can be seriously flawed*J, and understanding and integrating formal The growing number of empirical studies performed in ecology and evolution creates a need for quantitative summaries of research domains to generate higherorder conclusions about general trends and patterns. Recent developments in meta-analysis (the area of statistics that is designed for summarizing and analyzing multiple independent studies) have opened up new and exciting possibilities.
A Guide to Conducting a Meta-Analysis
Meta-analysis is widely accepted as the preferred method to synthesize research findings in various disciplines. This paper provides an introduction to when and how to conduct a meta-analysis. Several practical questions, such as advantages of meta-analysis over conventional narrative review and the number of studies required for a meta-analysis, are addressed. Common meta-analytic models are then introduced. An artificial dataset is used to illustrate how a meta-analysis is conducted in several software packages. The paper concludes with some common pitfalls of meta-analysis and their solutions. The primary goal of this paper is to provide a summary background to readers who would like to conduct heir first meta-analytic study.
Meta-analysis: Conceptual bases, statistical analysis and interpretation
2020
The term meta-analysis was first used by G.V. Glass in 1976 in an article called "Primary, secondary and meta-analysis of investigations" ("Primaria, secundaria y meta-análisis de la investigación"). He used this term to refer to the statistical analysis of all the results obtained in different clinical studies regarding the same subject and that were to be analyzed together. At the beginning, this type of analysis was mainly used for the examination of social studies and psychology investigations, but later, during the 1980s, it became a popular method used in medicine; particularly in the cardiovascular, cancer and perinatal specialties. Nowadays it is not rare to find several medical articles using this method. For this study we decided to perform a meta-analysis and also combine the results of the studies because when the sample size increases, the statistical potential increases as well. Furthermore, when including studies and researches performed in different Health Centers, the results obtained can be easily generalized. Nevertheless, the meta-analysis method has its controversies, many of them due to an excessive use of the method together with a lack of methodological rigor; there are many limitations to be considered when evaluating the results of a meta-analysis. In this article we will focus mainly on the statistical aspects of the subject, from the point of view of the description of the methods, indications and interpretations, without specifying other details such as the protocols for carrying out a systematic review or statistical formulas. The focus will be on the analytical methods used in meta-analyses of controlled clinical trials evaluating therapeutic efficacy or adverse reactions.
This supplement draws primarily on Chapters 5, 7 and 9.
A consumer's guide to meta-analysis
Arthritis Care & Research, 1997
Meta-analysis, an analysis that statistically pools the results from previous studies into a single quantitative analysis, has been described by one proponent as providing the very highest level of evidence for treatment efficacy (1). This type of analysis has an extensive literature (2-6) and has become a commonly employed tool in medical research. It is often used to evaluate collections of clinical trials (7,8), but has also been used to pool epidemiologic studies (9). The aim of this article is to provide a brief listing of the issues that should be considered in the construction of a solid meta-analysis. How these issues were addressed needs to be featured in the report from such a meta-analysis, and I will discuss what should be included in such a report. This is intended to help readers in critical evaluation of published meta-analyses, as well as provide guidelines on how to report a meta-analysis of one's own. Brief explanations of the statistical issues involved in the combination of studies will be given, but readers who wish to perform their own meta-analyses should consult the source materials listed in the references for full explanations of the techniques, limitations, and interpretations of meta-analysis.