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Subject: search.filters.subject.Statistical inference

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    Rapid Antigen Tests (RATs) and COVID-19 prevalence
    (OSF Preprins, 2022-05-04) Perezgonzalez J
    The article contains a Bayesian analysis to model expected rate of positive and negative COVID-19 cases, based on Rapid Antigen Test performance and COVID-19 prevalence in New Zealand. The results suggest that the majority of approved tests were excellent in identifying negative cases but might turn out too many false positives. Recommendations for a protocol for RAT-based testing concludes the article.
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    Where are our false positives?
    (OSF Preprints, 2022-05-03) Perezgonzalez J
    In our current regime of COVID-19 testing, a question seems not to be asked: Are we inferring the best we can from our results? Or, put differently, are we testing with severity? This study thus explore the proportion of expected positives and negative cases, with an especial focus on estimating false positives in isolation and estimating false (or unknown) negatives in the remaining population. Both seems to have been chiefly ignored by Government health policy.
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    The fallacy of placing confidence in confidence intervals – A commentary
    (Open Science Framework (OSF), 2/05/2017) Perezgonzalez JD
    ‘The fallacy of placing confidence in confidence intervals’ (Morey et al., 2016, Psychonomic Bulletin & Review, doi: 10.3758/s13423-015-0947-8) delved into a much needed technical and philosophical dissertation regarding the differences between typical (mis)interpretations of frequentist confidence intervals and the typical correct interpretation of Bayesian credible intervals. My contribution here partly strengthens the authors’ argument, partly closes some gaps they left open, and concludes with a note of attention to the possibility that there may be distinctions without real practical differences in the ultimate use of estimation by intervals, namely when assuming a common ground of uninformative priors and intervals as ranges of values instead of as posterior distributions per se.