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首页> 外文期刊>Annals of physical and rehabilitation medicine. >A Bayesian analysis of non-significant rehabilitation findings: Evaluating the evidence in favour of truly absent treatment effects
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A Bayesian analysis of non-significant rehabilitation findings: Evaluating the evidence in favour of truly absent treatment effects

机译：A Bayesian analysis of non-significant rehabilitation findings: Evaluating the evidence in favour of truly absent treatment effects

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Background: Relying solely on null hypothesis significance testing (NHST) to investigate rehabilitation interventions may result in researchers erroneously concluding the absence of a treatment effect. Objective: We aimed to distinguish between truly null treatment effects and data that are insensitive to detecting treatment effects by calculating Bayes factors (BF_01s) for non-significant findings in the rehabilitation literature. Additionally, to examine associations between BF_01, sample size, and observed P-values. Method: We searched the Cochrane Database of Systematic Reviews for meta-analyses with "rehabilitation" as a keyword that clearly evaluated a rehabilitation intervention. We extracted means, standard deviations, and sample sizes for treatment and comparison groups for individual findings within 175 meta-analyses. Two independent investigators classified the interventions into 4 categories using the Rehabilitation Treatment Specification System. We calculated t-statistics and associated P-values for each finding in order to extract non-significant results (P > 0.05). We calculated BF_01s for 5790 non-significant results and classified BF_01s based on the strength of evidence in favour of the null hypothesis (i.e., anecdotal, moderate, and strong) across and within intervention types. We examined correlations between BF01, sample size, and P-values across and within intervention types.

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