Search results
Results from the WOW.Com Content Network
Meta-analysis leads to a shift of emphasis from single studies to multiple studies. It emphasizes the practical importance of the effect size instead of the statistical significance of individual studies. This shift in thinking has been termed "meta-analytic thinking". The results of a meta-analysis are often shown in a forest plot.
The PRISMA flow diagram, depicting the flow of information through the different phases of a systematic review. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is an evidence-based minimum set of items aimed at helping scientific authors to report a wide array of systematic reviews and meta-analyses, primarily used to assess the benefits and harms of a health care ...
Metascience (also known as meta-research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency . It is also known as "research on research" and "the science of science", as it uses research methods to study how research is done and find where ...
The terms random-effect meta-regression and mixed-effect meta-regression are equivalent. Although calling one a random-effect model signals the absence of fixed effects, which would technically disqualify it from being a regression model, one could argue that the modifier random-effect only adds to, not takes away from, what any regression model should include: fixed effects.
In an IPD meta-analysis, patient-level data from multiple studies or settings are combined to address a certain research question. IPD meta-analyses tend to be common for large-scale and international projects, and they are less limited than aggregate data (AD) meta-analyses in terms of the availability and quality of data they can use. [2]
In statistics, (between-) study heterogeneity is a phenomenon that commonly occurs when attempting to undertake a meta-analysis. In a simplistic scenario, studies whose results are to be combined in the meta-analysis would all be undertaken in the same way and to the same experimental protocols.
Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...
Seed-based d mapping (formerly Signed differential mapping) or SDM is a statistical technique created by Joaquim Radua for meta-analysis studies assessing differences in brain activity or structure via neuroimaging techniques such as fMRI, VBM, DTI or PET. It may also refer to a specific piece of software created by the SDM Project to carry out ...