Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Likelihood-based Alternative to Null Hypothesis Significance Testing   The logical and practical difficulties associated with research
interpretation using P values and null hypothesis significance testing have
been extensively documented. This paper describes an alternative,
likelihood-based approach to P-value interpretation. The P-value and sample
size of a research study are used to derive a likelihood function with a single
parameter, the estimated population effect size, and the method of maximum
likelihood estimation is used to calculate the most likely effect size.
Comparison of the likelihood of the most likely effect size and the likelihood
of the minimum clinically significant effect size using the likelihood ratio
test yields the clinical significance support level (or S-value), a logical and
easily understood metric of research evidence. This clinical significance
likelihood approach has distinct advantages over null hypothesis significance
testing. As motivating examples we demonstrate the calculation and
interpretation of S-values applied to two recent widely publicised trials,
WOMAN from the Lancet and RELIEF from the New England Journal of Medicine.

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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: physics
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The categories of this paper are: chem-ph
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The categories of this paper are: supr-con
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The categories of this paper are: q-bio
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The categories of this paper are: econ
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The categories of this paper are: mtrl-th