Great claims are sometimes made for the inherent ability of the Bayesian framework to handle network meta-analysis and its greater flexibility. It emphasizes the practical importance of the effect size instead of the statistical significance of individual studies.
The need to integrate findings from many studies ensures that meta-analytic research is desirable and the large body of research now generated makes the conduct of this research feasible. Abstract The objectives of this paper are to provide an introduction to meta-analysis and to discuss the rationale for this type of research and other general considerations.
Thus it appears that in small meta-analyses, an incorrect zero between study variance estimate is obtained, leading to a false homogeneity assumption. This means that the greater this variability in effect sizes otherwise known as heterogeneitythe greater the un-weighting and this can reach a point when the random effects meta-analysis result becomes simply the un-weighted average effect size across the studies.
Further research around this framework is required to determine if this is indeed superior to the Bayesian or multivariate frequentist frameworks.
The alternative methodology uses complex statistical modelling to include the multiple arm trials and comparisons simultaneously between all competing treatments. At the other extreme, when all effect sizes are similar or variability does not exceed sampling errorno REVC is applied and the random effects meta-analysis defaults to simply a fixed effect meta-analysis only inverse variance weighting.
This is simply the weighted average of the effect sizes of a group of studies. AD is more commonly available e. Meta-analysis has been used to give helpful insight into: On the other hand, indirect aggregate data measures the effect of two treatments that were each compared against a similar control group in a meta-analysis.
In meta-analysis, effect sizes should also be reported with: Random effects model[ edit ] A common model used to synthesize heterogeneous research is the random effects model of meta-analysis.
However the relation between A and B is only known indirectly, and a network meta-analysis looks at such indirect evidence of differences between methods and interventions using statistical method. This assumption is typically unrealistic as research is often prone to several sources of heterogeneity; e.
The availability of a free software MetaXL  that runs the IVhet model and all other models for comparison facilitates this for the research community. The need to arrive at decisions affecting clinical practise fostered the momentum toward "evidence-based medicine" 1 — 2.
For example, the mvmeta package for Stata enables network meta-analysis in a frequentist framework. To do this a synthetic bias variance is computed based on quality information to adjust inverse variance weights and the quality adjusted weight of the ith study is introduced.
A meta-analysis of such expression profiles was performed to derive novel conclusions and to validate the known findings. The specification of the outcome and hypotheses that are tested is critical to the conduct of meta-analyses, as is a sensitive literature search.
By using meta-analysis, a wide variety of questions can be investigated, as long as a reasonable body of primary research studies exist. For more information about calculating effect sizes and confidence intervals, see: Very recently, automation of the three-treatment closed loop method has been developed for complex networks by some researchers  as a way to make this methodology available to the mainstream research community.
A recent evaluation of the quality effects model with some updates demonstrates that despite the subjectivity of quality assessment, the performance MSE and true variance under simulation is superior to that achievable with the random effects model.
Meta-analysis provides a systematic overview of quantitative research which has examined a particular question. For example, if treatment A and treatment B were directly compared vs placebo in separate meta-analyses, we can use these two pooled results to get an estimate of the effects of A vs B in an indirect comparison as effect A vs Placebo minus effect B vs Placebo.
Researchers willing to try this out have access to this framework through a free software. IPD evidence represents raw data as collected by the study centers.
Therefore, meta-analysis, a statistical procedure that integrates the results of several independent studies, plays a central role in evidence-based medicine.
There are many different types of effect size, but they fall into two main types: This has not been popular because the process rapidly becomes overwhelming as network complexity increases. This is important because much research has been done with single-subject research designs.While normally all publication manuals suggest citing original research papers, and only in case if research paper is not accessible, one should cite the review paper, with reference to research.
A research paper is one where an original study has been performed. A review paper may be either a narrative review, a systematic review or a meta-analysis. The objectives of this paper are to provide an introduction to meta-analysis and to discuss the rationale for this type of research and other general considerations.
Methods used to produce a rigorous meta-analysis are highlighted and some aspects of presentation and interpretation of meta-analysis.
Research Paper. Navigation. As you conduct research, ask yourself the following questions--What can this source do for you? How will you use this evidence? As background or to provide a context? To introduce and situate your thesis within existing conversation on topic? The historical roots of meta-analysis can be traced back to 17th century studies of astronomy, while a paper published in by the statistician Karl Pearson in the British Medical Journal One approach frequently used in meta-analysis in health care research is termed 'inverse variance method'.
Meta-analysis is a statistical technique for amalgamating, summarising, and reviewing previous quantitative research.
By using meta-analysis, a wide variety of questions can be investigated, as long as a reasonable body of primary research studies exist.Download