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Reproducibility probability estimation for testing statistical hypotheses

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  • De Martini, Daniele

Abstract

The applications of statistical tests often generate problems, because of their randomness. Here, stemming from the variability of statistical tests, the reproducibility probability of a statistically significant result () is estimated first. Then, statistical tests are defined on the basis of estimation. Lower bounds for , and then pointwise estimates are used. It is emphasized that the threshold for the pointwise estimator to define statistical tests turns out to be 1/2. Hence, taking the perspective of estimation, one can compute statistical tests and have suitable interpretations of their results.

Suggested Citation

  • De Martini, Daniele, 2008. "Reproducibility probability estimation for testing statistical hypotheses," Statistics & Probability Letters, Elsevier, vol. 78(9), pages 1056-1061, July.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:9:p:1056-1061
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    Cited by:

    1. Eleni Verykouki & Christos T. Nakas, 2023. "Adaptations on the Use of p -Values for Statistical Inference: An Interpretation of Messages from Recent Public Discussions," Stats, MDPI, vol. 6(2), pages 1-13, April.
    2. De Capitani, L. & De Martini, D., 2011. "On stochastic orderings of the Wilcoxon Rank Sum test statistic--With applications to reproducibility probability estimation testing," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 937-946, August.
    3. Bagnato, Luca & De Capitani, Lucio & Mazza, Angelo & Punzo, Antonio, 2015. "SDD: An R Package for Serial Dependence Diagrams," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(c02).
    4. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Detecting serial dependencies with the reproducibility probability autodependogram," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 35-61, January.
    5. Lucio De Capitani & Daniele De Martini, 2021. "Improving reproducibility probability estimation and preserving RP-testing," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 49-77, March.
    6. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2017. "A diagram to detect serial dependencies: an application to transport time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 581-594, March.

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