4 Matching Annotations
  1. Oct 2020
  2. erj.ersjournals.com erj.ersjournals.com
    Performance of Prediction Models for Covid-19: The Caudine Forks of the External Validation
    1
    1. ErikStuchly 17 Oct 2020

      Martin, G. P., Sperrin, M., & Sotgiu, G. (2020). Performance of Prediction Models for Covid-19: The Caudine Forks of the External Validation. European Respiratory Journal. https://doi.org/10.1183/13993003.03728-2020

      is:article lang:en COVID-19 epidemiology modeling prediction accuracy bias assisted decision making clinical implementation healthcare empirical evidence variability
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    erj.ersjournals.com/content/early/2020/10/08/13993003.03728-2020
  3. Aug 2020
  4. onlinelibrary.wiley.com onlinelibrary.wiley.com
    Statistical issues in the development a COVID‐19 prediction models
    1
    1. ErikStuchly 10 Aug 2020

      Collins, G. S., & Wilkinson, J. (n.d.). Statistical issues in the development a COVID-19 prediction models. Journal of Medical Virology, n/a(n/a). https://doi.org/10.1002/jmv.26390

      is:article lang:en COVID-19 epidemiology modeling flaw statistics diagnosis assessment prediction systematic review bias data quality reporting scientific practice bad science
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    onlinelibrary.wiley.com/doi/abs/10.1002/jmv.26390
  5. covid-19.iza.org covid-19.iza.org
    COVID-19 and the Labor Market
    1
    1. ErikStuchly 05 Aug 2020

      Exponential-​Growth Prediction Bias and Compliance with Safety Measures in the Times of COVID-19. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 5, 2020, from https://covid-19.iza.org/publications/dp13257/

      is:article lang:en COVID-19 prediction bias safety measure compliance transmission epidemiology exponential growth stage of outbreak communication statistics
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    covid-19.iza.org/publications/dp13257/
  6. Jun 2020
  7. bmcmedresmethodol.biomedcentral.com bmcmedresmethodol.biomedcentral.com
    Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction
    1
    1. edampf 03 Jun 2020

      Boulesteix, A., Strobl, C. Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction. BMC Med Res Methodol 9, 85 (2009). https://doi.org/10.1186/1471-2288-9-85

      is:article lang:en error rate estimation classifier negative bias high-dimensional prediction tuning parameter linear discriminant analysis bias source
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    bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-9-85