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• W2803772852 abstract "When discussing results medical research articles often tear substantive and statistical (methodical) contributions apart, just as if both were independent. Consequently, reasoning on bias tends to be vague, unclear and superficial. This can lead to over-generalized, too narrow and misleading conclusions, especially for causal research questions.To get the best possible conclusion, substantive and statistical expertise have to be integrated on the basis of reasonable assumptions. While statistics should raise questions on the mechanisms that have presumably created the data, substantive knowledge should answer them. Building on the related principle of Bayesian thinking, we make seven specific and four general proposals on writing a discussion section.Misinterpretation could be reduced if authors explicitly discussed what can be concluded under which assumptions. Informed on the resulting conditional conclusions other researchers may, according to their knowledge and beliefs, follow a particular conclusion or, based on other conditions, arrive at another one. This could foster both an improved debate and a better understanding of the mechanisms behind the data and should therefore enable researchers to better address bias in future studies." @default.
• W2803772852 created "2018-06-01" @default.
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• W2803772852 date "2018-04-17" @default.
• W2803772852 modified "2023-10-14" @default.
• W2803772852 title "Writing a discussion section: how to integrate substantive and statistical expertise" @default.
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• W2803772852 doi "https://doi.org/10.1186/s12874-018-0490-1" @default.
• W2803772852 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5905138" @default.
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