The Bias Dynamics Model: Correcting for Meta-Biases in Therapeutic Prediction

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Abstract
Inferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impact of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta-research evidence, the bias dynamics model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness.
Abstract ID :
PSA2022546
Submission Type

Associated Sessions

University of Alabama

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