8 research outputs found
Postnatal manganese exposure alters dopamine transporter function in adult rats: Potential impact on nonassociative and associative processes
Osteoarthritis of the Distal Interphalangeal and First Carpometacarpal Joints is Associated with High Bone Mass in Women and Small Bone Size and Low Lean Mass in Men
The Impact of ErbB2 on Cancer Progression and Metastasis through Modulation of Tumor and Tumor Microenvironment
Molecular Mechanisms of Curcumin in Neuroinflammatory Disorders: A Mini Review of Current Evidences
Non-Standard Errors
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants