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Research synthesis or evidence synthesis is the process of combining the results of multiple primary research studies aimed at testing the same conceptual hypothesis. It may be applied to either quantitative [1] or qualitative research. [2] Its general goals are to make the findings from multiple different studies more generalizable and ...
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 ...
A notable marker of primary research is the inclusion of a "methods" section, where the authors describe how the data was generated. Common examples of secondary research include textbooks, encyclopedias, news articles, review articles, and meta analyses. [2] [3]
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.
Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information ...
Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
Synthetic data is generated to meet specific needs or certain conditions that may not be found in the original, real data. One of the hurdles in applying up-to-date machine learning approaches for complex scientific tasks is the scarcity of labeled data, a gap effectively bridged by the use of synthetic data, which closely replicates real experimental data. [3]
An SDRF file is a tab-delimited file describing the relationships between samples, arrays, data, and other objects used or produced in a microarray investigation. For simple experimental designs, constructing the SDRF file is straightforward, and even complex loop designs can be expressed in this format.