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Author: search.filters.author.Perezgonzalez JHas files: No

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    Frequentist-Bayesian analyses in parallel using JASP - A tutorial
    (PsyArXiv, 2022-07-21) Perezgonzalez J
    A tutorial to demonstrate the use of parallel Frequentist-Bayesian analyses using JASP, and the plausible inferences one may be able to make from such combined analysis.
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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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    Severity Testing: A Primer
    (2020-04-01) Perezgonzalez J
    This is a primer on Mayo's severity testing technology, briefly explaining step by step the implications of severity in the context of rejection and retention of point nil hypotheses, of (conceptually broader) null hypotheses, and of confidence intervals. I finish proposing the use of a confidence interval heuristic for assessing Mayo's severity straightforwardly. In the present article we shall not concern ourselves with wars, whether statistical or philosophical. Instead, we shall work on a philosophical concept being put forth by Mayo in the last two decades (e.g., Mayo, 1983, 1991, 1996; Mayo & Spanos, 2006, 2010), more recently so with her book Statistical Inference as Severe Testing (Mayo, 2018). Severity testing stands for a procedure a researcher can avail of to falsify (frequentist) hypotheses; yet it may spill beyond that bin to become a broader philosophical approach that can serve to also falsify (Bayesian) models (Gelman & Shalizi, 2013), even entire theories. The article I present here is going to be a primer on Mayo’s severity concept in the frequentist realm. However, I sympathise with Gelman and reckon the unstated goal is to advance such primer as a step towards using severity in line with Gelman’s ideas and further, including Taleb’s own use of falsification as a tool to get more acquainted with what our models and theories prevents us from learning, such as about extreme events and Black Swans (e.g., Taleb, 2005, 2010).
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    Another Science Is Possible
    (Frontiers Media, 8/06/2020) Perezgonzalez J; Frias-Navarro D; Pascual-Llobell J; Dettweiler, U; Hanfstingl, B; Schroter, H
    The philosopher of science Isabelle Stengers provides some food for thought regarding both the way we are doing science and the need for an alternative approach likened to the slow movement in other spheres of life.