Reproducing Statistical Results

@inproceedings{Stodden2015ReproducingSR,
  title={Reproducing Statistical Results},
  author={Victoria Stodden},
  year={2015}
}
The reproducibility of statistical findings has become a concern not only for statisticians, but for all researchers engaged in empirical discovery. Section 2 of this article identifies key reasons statistical findings may not replicate, including power and sampling issues; misapplication of statistical tests; the instability of findings under reasonable perturbations of data or models; lack of access to methods, data, or equipment; and cultural barriers such as researcher incentives and… 

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References

SHOWING 1-10 OF 95 REFERENCES

Why Most Published Research Findings Are False

TLDR
Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true.

A Systematic Statistical Approach to Evaluating Evidence from Observational Studies

TLDR
Some of the challenges encountered in observational studies are reviewed and an alternative, data-driven approach to observational study design, execution, and analysis is reviewed.

Revised standards for statistical evidence

  • V. Johnson
  • Computer Science
    Proceedings of the National Academy of Sciences
  • 2013
TLDR
Modifications of common standards of evidence are proposed to reduce the rate of nonreproducibility of scientific research by a factor of 5 or greater and to correct the problem of unjustifiably high levels of significance.

False-Positive Psychology

TLDR
It is shown that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings, flexibility in data collection, analysis, and reporting dramatically increases actual false- positive rates, and a simple, low-cost, and straightforwardly effective disclosure-based solution is suggested.

A peculiar prevalence of p values just below .05

In null hypothesis significance testing (NHST), p values are judged relative to an arbitrary threshold for significance (.05). The present work examined whether that standard influences the

Discovering Findings That Replicate From a Primary Study of High Dimension to a Follow-Up Study

We consider the problem of identifying whether findings replicate from one study of high dimension to another, when the primary study guides the selection of hypotheses to be examined in the

Scientific Utopia

TLDR
Strategies for improving scientific practices and knowledge accumulation are developed that account for ordinary human motivations and biases and can reduce the persistence of false findings.

Interpreting observational studies: why empirical calibration is needed to correct p-values

TLDR
This experiment provides evidence that the majority of observational studies would declare statistical significance when no effect is present, and empirical calibration was found to reduce spurious results to the desired 5% level.

Again, and Again, and Again …

. . . Replication—The confirmation of results and conclusions from one study obtained independently in another—is considered the scientific gold standard. New tools and technologies, massive amounts
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