Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in 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 (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Safety of etoricoxib, celecoxib and non-selective NSAIDs in Ankylosing spondylitis and other Spondyloarthritis patients: A Swedish national population based cohort study.

Objective: Safety data regarding the usage of etoricoxib and other nonsteroidal anti-inflammatory drugs (NSAIDs) in ankylosing spondylitis (AS) and other spondyloarthritis (SpA) patients are rather limited. To estimate and compare rates of gastrointestinal, renovascular, and cardiovascular adverse events in patients exposed to etoricoxib, celecoxib, non-selective NSAIDs (nsNSAIDs) or totally unexposed to NSAIDs. Methods: This is a national register-based cohort study on patients with AS or SpA (N=21,872) identified in the Swedish national patient register (NPR) 1987 - 2009. Treatment exposure was assessed time-dependently based on the prescription drugs register from 2006 - 2009 adjusting for socio-demography, and comorbidities derived from national population-based registers. Results: Exposure to etoricoxib, celecoxib and nsNSAID were 7.6%, 3.9% and 71.2%, respectively. No major risk differences for serious cardiovascular, gastrointestinal or renal adverse events were seen among the three exposure groups. Patients unexposed to NSAIDs had more baseline co-morbidities and an increased relative risk for congestive heart failure events during the study period 2.0 (95% 1.3 to 3.2). The relative risk for atherosclerotic events was non-significant when compared to the nsNSAID group 1.0 (95% CI: 0.7 to 1.5), while the risk for gastrointestinal events was lower for unexposed patients 0.5 (0.4 to 0.7). Conclusion: Overall, serious adverse events related to nsNSAID, etoricoxib and celecoxib were similar and in the range of what would be expected in a group of SpA patients. Patients unexposed to NSAIDs had considerable more baseline co-morbidities and increased risk for congestive heart failure, reflecting a selection of patients being prescribed NSAID in clinical practice. This article is protected by copyright. All rights reserved

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

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in 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 (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants