Likelihood methods for measuring statistical evidence.

@article{Blume2002LikelihoodMF,
  title={Likelihood methods for measuring statistical evidence.},
  author={Jeffrey D Blume},
  journal={Statistics in medicine},
  year={2002},
  volume={21 17},
  pages={2563-99}
}
Focused on interpreting data as statistical evidence, the evidential paradigm uses likelihood ratios to measure the strength of statistical evidence. Under this paradigm, re-examination of accumulating evidence is encouraged because (i) the likelihood ratio, unlike a p-value, is unaffected by the number of examinations and (ii) the probability of observing strong misleading evidence is naturally low, even for study designs that re-examine the data with each new observation. Further, the… CONTINUE READING
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On the probability of observing misleading statistical evidence (with discussion)

  • RM Royall
  • Journal of the American Statistical Association
  • 2000
Highly Influential
16 Excerpts

On the probability of observing misleading evidence in sequential trials

  • JD Blume
  • 2001
Highly Influential
6 Excerpts

Statistical Evidence: A Likelihood Paradigm

  • RM Royall
  • Annals of Human Genetics
  • 1997
Highly Influential
10 Excerpts

Discussion of On the Probability of Observing Misleading Statistical Evidence by RM Royall

  • RL Wolpert
  • Journal of the American Statistical Association
  • 2000

Review of R. Royall (1997) statistical evidence: a likelihood paradigm

  • VJ Vieland, SE Hodge
  • Annals of Human Genetics
  • 1998
1 Excerpt

Review of R . Royall (

  • VJ Vieland, SE Hodge
  • 1997

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