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Meta-Analysis and Systematic Reviews
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How to Produce a Systematic Review or a Meta Analysis
Systematic Reviews and Meta-Analyses: A Step-By-Step Guide
Centre for Cognitive Aging and Cognitive Epidemology
A systematic review answers a defined research question by collecting and summarising all empirical evidence that fits pre-specified eligibility criteria.
A meta-analysis is the use of statistical methods to summarise the results of these studies.
Step 1: Why do a systematic review?
Step 2: Who will be involved?
Step 3: Formulate the problem. Has it been done before?
Registering your review.
Step 4: Perform your search.
Step 5: Data extraction.
Step 6: Critical appraisal of studies (quality assessment).
Step 7 Data synthesis.
Step 8: Presenting results (writing the report).
Step 9: Archiving and updating.
Lecture 1: Introduction to systematic reviews
Lecture 2: Systematic literature searching
Lecture 3: Systematic review hints and tips
Lecture 3: Introduction to meta-analysis
In statistics, meta-analysis comprises statistical methods for contrasting and combining results from different studies in the hope of identifying patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies. Meta-analysis can be thought of as “conducting research about previous research.” In its simplest form, meta-analysis is done by identifying a common statistical measure that is shared between studies, such as effect size or p-value, and calculating a weighted average of that common measure. This weighting is usually related to the sample sizes of the individual studies, although it can also include other factors, such as study quality.
The motivation of a meta-analysis is to aggregate information in order to achieve a higher statistical power for the measure of interest, as opposed to a less precise measure derived from a single study. In performing a meta-analysis, an investigator must make choices many of which can affect its results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, and accounting for or choosing not to account for publication bias. 
Meta-analyses are often, but not always, important components of a systematic review procedure. For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works. Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use “meta-analysis” to refer to statistical methods of combining evidence, leaving other aspects of ‘research synthesis’ or ‘evidence synthesis’, such as combining information from qualitative studies, for the more general context of systematic reviews.
3.1 Publication bias: the file drawer problem
3.2 Agenda-driven bias
4 Steps in a meta-analysis
5 Methods and assumptions
5.2 Statistical models
5.2.1 Fixed effects model
5.2.2 Random effects model
5.2.3 Quality effects model
5.2.4 IVhet model
6 Applications in modern science
7 See also
9 Further reading
10 External links
Systematic Review Methods
The Community Guide
What is a systematic review?
A systematic review is a review of scientific studies on a specific topic. It uses a formal process to:
Identify all relevant studies
Assess their quality
Summarize the evidence
Why do a systematic review?
Systematic reviews help make sense of large bodies of scientific literature by applying the scientific process to:
Reduce bias in how conclusions are reached
Improve the power and precision of results
Summarize evidence about the effectiveness of particular approaches for addressing a public health problem
Analyze generalizability of findings
Identify knowledge gaps and need for additional research
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