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Statistical significance or clinical significance? A researcher's dilemma for appropriate interpretation of research results

It is incredibly essential that the current clinicians and researchers remain updated with findings of current biomedical literature for evidence-based medicine. However, they come across many types of research that are nonreproducible and are even difficult to interpret clinically. Statistical and...

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Detalles Bibliográficos
Autor principal: Sharma, Hunny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477766/
https://www.ncbi.nlm.nih.gov/pubmed/34658732
http://dx.doi.org/10.4103/sja.sja_158_21
Descripción
Sumario:It is incredibly essential that the current clinicians and researchers remain updated with findings of current biomedical literature for evidence-based medicine. However, they come across many types of research that are nonreproducible and are even difficult to interpret clinically. Statistical and clinical significance is one such difficulty that clinicians and researchers face across many instances. In simpler terms, the P value tests all hypothesis about how the data were produced (model as whole), and not just the targeted hypothesis that it is intended to test (such as a null hypothesis) keeping in mind how reliable are the of the research results. Most of the times it is misinterpreted and misunderstood as a measure to judge the results as clinically significant. Hence this review aims to impart knowledge about “P” value and its importance in biostatistics, also highlights the importance of difference between statistical and clinical significance for appropriate interpretation of research results.