![]() ![]() In particular in changing patterns describing P values just above 0.05 value. If this ‘new statistics’ approach has worked out well should be reflected in the phases describing non-significance results of RCTs. Since 2005 there is an increasing concern that most current published research findings are false and it has been generally advised to switch from null hypothesis significance testing to using effect sizes, estimation, and cumulation of evidence. This phrasing may convince readers about the value of their work. Sometimes, creativity and inventive strategies of clinical researchers may be used – describing their clinical results to be ‘almost significant’ – to get their data published. ![]() ![]() This may be at least partially related to the statistical paradigm of the 0.05 significance threshold. Misreporting and misinterpretation are urgent problems in RCT output. Significance statement The power of language to modify the reader’s perception of how to interpret biomedical results cannot be underestimated. ![]()
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