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Charlotte Braima
Ealuatingevidence….docx
Summary
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Discussion
There are various approaches to examining evidence. Meta-analysis and Systematic
reviews are the main and most common methods of evaluating evidence. These methods assist in assist, assistance (help): assist help
Discussion
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determining the validity and relevance of the evidence. Meta-analysis and Systematic reviews
are very reliable approaches to examining evidence levels and are widely used by researchers.
The two approaches of evaluating evidence have some similarities and differences.
The following are the similarities between meta-analysis and systematic reviews. Both
methods are believed to be the highest quality of evidence for decision-making in the clinical
setting and can be utilized above all the other approaches of evidence evaluation (Singh, 2017).
Both meta-analysis and systematic reviews involve data collection from different sources and
then summarize the results and evidence of the various study articles.
However, the two methods have numerous differences. Systematic reviews involve
collecting and summarising all the empirical evidence, while the meta-analysis method uses
statistical approaches when summarizing results from studies. A meta-analysis method is a
statistical approach utilized to combine the numerical results and findings from studies when
possible; however, the systematic review method is a systematic, formal and structured method
of reviewing all the topic’s relevant literature (Wu, Song, & Zhao, 2018). The meta-analysis
rationale is that through sample combination from various samples of different studies, the
overall sample size is enhanced, for reliable findings, while the rationale for systemic reviews is
that pooling data together from various sources can result in greater information reliability.
References
Singh, S. (2017). How to conduct and interpret systematic reviews and meta-analyses. Clinical
and translational gastroenterology, 8(5), e93.
Wu, W., Song, Y., & Zhao, W. (2018). Evaluating evidence reliability on the basis of
intuitionistic fuzzy sets. Information, 9(12), 298.
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References