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Meta-analysis is a method of synthesis of quantitative data from multiple independent studies addressing a common research question. An important part of this method involves computing a combined effect size across all of the studies.
The aim of the PRISMA statement is to help authors improve the reporting of systematic reviews and meta-analyses. [3] PRISMA has mainly focused on systematic reviews and meta-analysis of randomized trials, but it can also be used as a basis for reporting reviews of other types of research (e.g., diagnostic studies, observational studies).
Metascience seeks to identify poor research practices, including biases in research, poor study design, abuse of statistics, and to find methods to reduce these practices. [1] Meta-research has identified numerous biases in scientific literature. [17] Of particular note is the widespread misuse of p-values and abuse of statistical significance ...
A systematic review is a scholarly synthesis of the evidence on a clearly presented topic using critical methods to identify, define and assess research on the topic. [1] A systematic review extracts and interprets data from published studies on the topic (in the scientific literature), then analyzes, describes, critically appraises and summarizes interpretations into a refined evidence-based ...
A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...
In medical research, an umbrella review is a review of systematic reviews or meta-analyses. [1] [2] [3] They may also be called overviews of reviews, reviews of reviews, summaries of systematic reviews, or syntheses of reviews. [1] Umbrella reviews are among the highest levels of evidence currently available in medicine. [2]
Meta-analysis is a method used to combine the results of different trials in order to obtain a quantitative synthesis. The size of individual clinical trials is often too small to detect treatment effects reliably. Meta-analysis increases the power of statistical analyses by pooling the results of all available trials.
The original authors and database curators then become responsible for metadata creation, with the assistance of automated processes. Comprehensive metadata for all experimental data is the foundation of the FAIR Guiding Principles, or the standards for ensuring research data are findable, accessible, interoperable, and reusable. [61]