A likelihood-based approach to P -value interpretation provided a novel, plausible, and clinically useful research study metric

Adams, Nicholas G; O’Reilly, Gerard

doi:10.1016/j.jclinepi.2017.08.016

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…In a recent issue of the JCE, Adams and O'Reilly presented a creative approach to inference and communication of scientific results [1]. Having explored a similar methodology in my own ongoing work in this area, I offer some critical thoughts on their paper.…”

Section: The Delta Likelihood Ratio Does Not Incorporate Study Powermentioning

confidence: 99%

“…Note that restriction to a one-sided alternative is essential for producing a unimodal likelihood function given any divergence of the data from the null [6] and forms the basis of the authors' dLR framework. Here an additional methodological issue arises in that they appear to have used two-sided P-values from the literature in their Table 2 to present dLRs ostensibly interpreted in favor of a one-sided alternative [1].…”

Section: Rz Powermentioning

confidence: 99%

“…We thank the author for his interesting critique of our paper [1]. With regard to the false positive rate being dependent on alpha rather than the P-value, we point out that alpha is set to be equivalent to the P-value; thus, the two equations shown in the letter are identical.…”

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confidence: 99%

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The delta likelihood ratio does not incorporate study power

Phelan

2018

Journal of Clinical Epidemiology

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Section: The Delta Likelihood Ratio Does Not Incorporate Study Powermentioning

confidence: 99%

Section: Rz Powermentioning

confidence: 99%

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The delta likelihood ratio does not incorporate study power

Phelan

2018

Journal of Clinical Epidemiology

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“…[252]. Despite the wide use of p-value in research study, there are certain limitations such as, it ignores the concept of prior probability and power of the study [254]. Likewise, specificity only provides the true negative rate, e.g., proportion of non-seizure EEG that correctly classified as nonseizure.…”

Section: Discussionmentioning

confidence: 99%

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

Awal¹

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Neonatal Hypoxic Ischaemic Encephalopathy (HIE) is a major cause of morbidity and mortality in newborns throughout the world with an incidence of 1-8/1000 newborns in developed countries and up to 26/1000 newborns in developing countries. It causes one million neonatal deaths globally per year. Electroencephalography (EEG) is a useful method for assessment of brain activity in newborns with HIE. EEG performs well in the early diagnosis and classification of HIE severity and in predicting neurodevelopmental outcome. A normal EEG is highly predictive of a normal outcome and various abnormal EEG features are associated with neurological abnormalities or death.A systematic review and meta-analysis of the literature was undertaken to determine which specific background features of the EEG best predict outcome (Aim 1). Automatic detection and classification

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The Delta likelihood ratio does not incorporate study power. Author response

Adams

2018

Journal of Clinical Epidemiology

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Imputation of the observed P-value and effect size within the likelihood ratio and power function are together a maneuver to recenter the H A distribution about the observed estimate ð b dÞ. As the authors imply, this effectively reconfigures their alternative hypothesis from the composite H A : dO0 to the simple HThe resulting likelihood ratio (their dLR) is thus maximized and represents an upper bound on the evidence against H 0 for the one-sided case. Furthermore, reparameterization of the power function in this manner fixes ''marginal power'' at 0.5 for all cases, invalidating the authors' assertion that ''the dLR incorporates study power,'' as it is merely a transformation of the P-value.Similar approaches to determining the Bayes factor bound for a given P-value have been longstanding in the Bayesian literature [7e9], where distributed priors yield average power ð1 À bÞ in the predata expressions [4]. In the present case, however, evaluation of the evidence relative to the a posteriori H 0 A divorces inference from any prior effect estimate, from which power would have been computed. Recognition of the dLR as a bound for the a priori composite H A will prevent its misinterpretation as an externally valid (regarding priors) measure of evidence.

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A likelihood-based approach to P -value interpretation provided a novel, plausible, and clinically useful research study metric

Cited by 4 publications

References 20 publications

The delta likelihood ratio does not incorporate study power

The delta likelihood ratio does not incorporate study power

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

The Delta likelihood ratio does not incorporate study power. Author response

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