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STATISTICS IN TRANSITION

ISSN:

1234-7655

eISSN:

2450-0291

Website:

https://sit.stat.gov.pl/ open in new tab

Publisher:

Główny Urząd Statystyczny

Disciplines
(Field of Science):

  • economics and finance (Social studies)
  • management and quality studies (Social studies)
  • sociology (Social studies)
  • mathematics (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2024 70 Ministry scored journals list 2024
Ministry points - previous years
Year Points List
2024 70 Ministry scored journals list 2024
2023 70 Ministry Scored Journals List
2022 70 Ministry Scored Journals List 2019-2022
2021 70 Ministry Scored Journals List 2019-2022
2020 70 Ministry Scored Journals List 2019-2022
2019 70 Ministry Scored Journals List 2019-2022
2018 15 B
2017 15 B
2016 15 B
2015 15 B
2014 9 B
2013 9 B
2012 8 B
2011 8 B
2010 9 B

Model:

Open Access

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2023 1
Points CiteScore - previous years
Year Points
2023 1
2022 0.9
2021 0.7
2020 0.4
2019 0.5
2018 0.4
2017 0.2
2016 0.1
2015 0

Impact Factor:

n/a

Publishing policy:

License: CC BY-NC-ND 4.0
License
Creative Commons: BY-NC-ND 4.0 open in new tab
Information on publishing policy
https://sit.stat.gov.pl/ForAuthors open in new tab
Information on the conditions of self-archiving
Included in license
Is self-archiving allowed by the journal?
Yes - with restrictions
Submitted Version Help
no
Accepted Version Help
no
Published Version Help
yes
Self-archiving places
Non-Commercial Services
Repository for Scientific Papers
Institutional Repository
Institutional Website
Author's Homepage
Information on research data policy
n/a
Months of embargo
no embargo
Additional information
Must link to journal homepage with DOI.
Self-archiving policy based on correspondence with the editors.

Papers published in journal

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total: 1

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Catalog Journals

Year 2024
  • The shape of an ROC curve in the evaluation of credit scoring models
    Publication

    - STATISTICS IN TRANSITION - Year 2024

    The AUC, i.e. the area under the receiver operating characteristic (ROC) curve, or its scaled version, the Gini coefficient, are the standard measures of the discriminatory power of credit scoring. Using binormal ROC curve models, we show how the shape of the curves affects the economic benefits of using scoring models with the same AUC. Based on the results, we propose that the shape parameter of the fitted ROC curve is reported...

    Full text available to download

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