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  1. Article: Evidence from marginally significant

    Johnson, Valen E

    The American statistician

    2019  Volume 73, Issue Suppl 1, Page(s) 129–134

    Abstract: This article examines the evidence contained ... ...

    Abstract This article examines the evidence contained in
    Language English
    Publishing date 2019-03-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2064982-4
    ISSN 1537-2731 ; 0003-1305
    ISSN (online) 1537-2731
    ISSN 0003-1305
    DOI 10.1080/00031305.2018.1518788
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Raise the bar rather than retire significance.

    Johnson, Valen E

    Nature

    2019  Volume 567, Issue 7749, Page(s) 461

    MeSH term(s) Data Interpretation, Statistical
    Language English
    Publishing date 2019-03-20
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 120714-3
    ISSN 1476-4687 ; 0028-0836
    ISSN (online) 1476-4687
    ISSN 0028-0836
    DOI 10.1038/d41586-019-00970-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  3. Article ; Online: Bayes factor functions for reporting outcomes of hypothesis tests.

    Johnson, Valen E / Pramanik, Sandipan / Shudde, Rachael

    Proceedings of the National Academy of Sciences of the United States of America

    2023  Volume 120, Issue 8, Page(s) e2217331120

    Abstract: Bayes factors represent a useful alternative ... ...

    Abstract Bayes factors represent a useful alternative to
    MeSH term(s) Bayes Theorem ; Research Design
    Language English
    Publishing date 2023-02-13
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.2217331120
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Efficient alternatives for Bayesian hypothesis tests in psychology.

    Pramanik, Sandipan / Johnson, Valen E

    Psychological methods

    2022  

    Abstract: Bayesian hypothesis testing procedures have gained increased acceptance in recent years. A key advantage that Bayesian tests have over classical testing procedures is their potential to quantify information in support of true null hypotheses. Ironically, ...

    Abstract Bayesian hypothesis testing procedures have gained increased acceptance in recent years. A key advantage that Bayesian tests have over classical testing procedures is their potential to quantify information in support of true null hypotheses. Ironically, default implementations of Bayesian tests prevent the accumulation of strong evidence in favor of true null hypotheses because associated default alternative hypotheses assign a high probability to data that are most consistent with a null effect. We propose the use of "nonlocal" alternative hypotheses to resolve this paradox. The resulting class of Bayesian hypothesis tests permits more rapid accumulation of evidence in favor of both true null hypotheses and alternative hypotheses that are compatible with standardized effect sizes of most interest in psychology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
    Language English
    Publishing date 2022-04-14
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2103345-6
    ISSN 1939-1463 ; 1082-989X
    ISSN (online) 1939-1463
    ISSN 1082-989X
    DOI 10.1037/met0000482
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  5. Article: A Hyperparameter-Free, Fast and Efficient Framework to Detect Clusters From Limited Samples Based on Ultra High-Dimensional Features.

    Rahman, Shahina / Johnson, Valen E / Rao, Suhasini Subba

    IEEE access : practical innovations, open solutions

    2022  Volume 10, Page(s) 116844–116857

    Abstract: Clustering is a challenging problem in machine learning in which one attempts to ... ...

    Abstract Clustering is a challenging problem in machine learning in which one attempts to group
    Language English
    Publishing date 2022-11-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2687964-5
    ISSN 2169-3536
    ISSN 2169-3536
    DOI 10.1109/access.2022.3218800
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: A Modified Sequential Probability Ratio Test.

    Pramanik, Sandipan / Johnson, Valen E / Bhattacharya, Anirban

    Journal of mathematical psychology

    2021  Volume 101

    Abstract: We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power. Examples are provided ... ...

    Abstract We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power. Examples are provided for
    Language English
    Publishing date 2021-03-04
    Publishing country United States
    Document type Journal Article
    ISSN 0022-2496
    ISSN 0022-2496
    DOI 10.1016/j.jmp.2021.102505
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  7. Article: On the Existence of Uniformly Most Powerful Bayesian Tests With Application to Non-Central Chi-Squared Tests.

    Nikooienejad, Amir / Johnson, Valen E

    Bayesian analysis

    2020  Volume 16, Issue 1, Page(s) 93–109

    Abstract: Uniformly most powerful Bayesian tests (UMPBT's) are an objective class of Bayesian hypothesis tests that can be considered the Bayesian counterpart of classical uniformly most powerful tests. Because the rejection regions of UMPBT's can be matched to ... ...

    Abstract Uniformly most powerful Bayesian tests (UMPBT's) are an objective class of Bayesian hypothesis tests that can be considered the Bayesian counterpart of classical uniformly most powerful tests. Because the rejection regions of UMPBT's can be matched to the rejection regions of classical uniformly most powerful tests (UMPTs), UMPBT's provide a mechanism for calibrating Bayesian evidence thresholds, Bayes factors, classical significance levels and p-values. The purpose of this article is to expand the application of UMPBT's outside the class of exponential family models. Specifically, we introduce sufficient conditions for the existence of UMPBT's and propose a unified approach for their derivation. An important application of our methodology is the extension of UMPBT's to testing whether the non-centrality parameter of a chi-squared distribution is zero. The resulting tests have broad applicability, providing default alternative hypotheses to compute Bayes factors in, for example, Pearson's chi-squared test for goodness-of-fit, tests of independence in contingency tables, and likelihood ratio, score and Wald tests.
    Language English
    Publishing date 2020-01-07
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2201249-7
    ISSN 1931-6690 ; 1936-0975
    ISSN (online) 1931-6690
    ISSN 1936-0975
    DOI 10.1214/19-ba1194
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  8. Article ; Online: Global Estimate of Human Brucellosis Incidence.

    Laine, Christopher G / Johnson, Valen E / Scott, H Morgan / Arenas-Gamboa, Angela M

    Emerging infectious diseases

    2023  Volume 29, Issue 9, Page(s) 1789–1797

    Abstract: Brucellosis is a major public health concern worldwide, especially for persons living in resource-limited settings. Historically, an evidence-based estimate of the global annual incidence of human cases has been elusive. We used international public ... ...

    Abstract Brucellosis is a major public health concern worldwide, especially for persons living in resource-limited settings. Historically, an evidence-based estimate of the global annual incidence of human cases has been elusive. We used international public health data to fill this information gap through application of risk metrics to worldwide and regional at-risk populations. We performed estimations using 3 statistical models (weighted average interpolation, bootstrap resampling, and Bayesian inference) and considered missing information. An evidence-based conservative estimate of the annual global incidence is 2.1 million, significantly higher than was previously assumed. Our models indicate Africa and Asia sustain most of the global risk and cases, although areas within the Americas and Europe remain of concern. This study reveals that disease risk and incidence are higher than previously suggested and lie mainly within resource-limited settings. Clarification of both misdiagnosis and underdiagnosis is required because those factors will amplify case estimates.
    MeSH term(s) Humans ; Bayes Theorem ; Incidence ; Africa ; Asia ; Brucellosis/epidemiology
    Language English
    Publishing date 2023-08-23
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 1380686-5
    ISSN 1080-6059 ; 1080-6040
    ISSN (online) 1080-6059
    ISSN 1080-6040
    DOI 10.3201/eid2909.230052
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Reply to Gelman, Gaudart, Pericchi: More reasons to revise standards for statistical evidence.

    Johnson, Valen E

    Proceedings of the National Academy of Sciences of the United States of America

    2014  Volume 111, Issue 19, Page(s) E1936–7

    MeSH term(s) Reproducibility of Results ; Statistics as Topic/standards
    Language English
    Publishing date 2014-05-28
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 209104-5
    ISSN 1091-6490 ; 0027-8424
    ISSN (online) 1091-6490
    ISSN 0027-8424
    DOI 10.1073/pnas.1400338111
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  10. Article: UNIFORMLY MOST POWERFUL BAYESIAN TESTS.

    Johnson, Valen E

    Annals of statistics

    2014  Volume 41, Issue 4, Page(s) 1716–1741

    Abstract: Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian ... ...

    Abstract Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian setting by defining uniformly most powerful Bayesian tests to be tests that maximize the probability that the Bayes factor, in favor of the alternative hypothesis, exceeds a specified threshold. Like their classical counterpart, uniformly most powerful Bayesian tests are most easily defined in one-parameter exponential family models, although extensions outside of this class are possible. The connection between uniformly most powerful tests and uniformly most powerful Bayesian tests can be used to provide an approximate calibration between
    Language English
    Publishing date 2014-03-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1476670-X
    ISSN 2168-8966 ; 0090-5364
    ISSN (online) 2168-8966
    ISSN 0090-5364
    DOI 10.1214/13-AOS1123
    Database MEDical Literature Analysis and Retrieval System OnLINE

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