User:EBMLibrarian/Evidence-based medicine
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- Publication bias: A judgment made on the basis of the question whether all the research evidence has been taken to account.[1]
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- "Trial design considerations: High-quality studies have clearly defined eligibility criteria and have minimal missing data.[2][3]
- Generalizability considerations: Studies may only be applicable to narrowly defined patient populations and may not be generalizable to other clinical contexts.[2]
- Follow-up: Sufficient time for defined outcomes to occur can influence the prospective study outcomes and the statistical power of a study to detect differences between a treatment and control arm.[4]
- Power: A mathematical calculation can determine whether the number of patients is sufficient to detect a difference between treatment arms. A negative study may reflect a lack of benefit, or simply a lack of sufficient quantities of patients to detect a difference."[2][5][4]
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- ^ DeVito, Nicholas J.; Goldacre, Ben (2019-04). "Catalogue of bias: publication bias". BMJ evidence-based medicine. 24 (2): 53–54. doi:10.1136/bmjebm-2018-111107. ISSN 2515-4478. PMID 30523135.
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(help) - ^ a b c Bellomo, Rinaldo; Bagshaw, Sean M. (2006). "Evidence-based medicine: classifying the evidence from clinical trials--the need to consider other dimensions". Critical Care (London, England). 10 (5): 232. doi:10.1186/cc5045. ISSN 1466-609X. PMC 1751050. PMID 17029653.
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: CS1 maint: unflagged free DOI (link) - ^ Greeley, Christopher (2016-12). "Demystifying the Medical Literature". Academic Forensic Pathology. 6 (4): 556–567. doi:10.23907/2016.055. ISSN 1925-3621. PMC 6474497. PMID 31239931.
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(help) - ^ a b Akobeng, A. K. (2005-08). "Understanding randomised controlled trials". Archives of Disease in Childhood. 90 (8): 840–844. doi:10.1136/adc.2004.058222. ISSN 1468-2044. PMC 1720509. PMID 16040885.
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(help) - ^ "Statistical Power". Bandolier. 2007.