Bayesian Mendelian randomization with an interval causal null hypothesis: ternary decision rules and loss function calibration

Bayesian Mendelian randomization with an interval causal null hypothesis: ternary decision rules and loss function calibration

Abstract We enhance the Bayesian Mendelian Randomization (MR) framework of Berzuini et al. (Biostatistics 21(1):86–101, 2018) by allowing for interval null causal hypotheses, where values of the causal effect parameter that fall within a user-specified interval of “practical equivalence” (ROPE) (Kru...

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Main Authors: Linyi Zou, Teresa Fazia, Hui Guo, Carlo Berzuini
格式: 文件
语言:English
出版: BMC 2024-01-01
丛编:BMC Medical Research Methodology
主题:
Mendelian randomization
Region of practical equivalence
Interval null hypothesis
Ternary decision logic
Loss function calibration
Juvenile myocardial infarction
在线阅读:https://doi.org/10.1186/s12874-023-02067-4

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https://doi.org/10.1186/s12874-023-02067-4

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