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Thomas Selhorst

Biographic Data

ID7802760
NAMEThomas Selhorst
GIVEN NAMESThomas
FAMILY NAMESelhorst
SIGNATURESELHORST T
AFFILIATIONSFederal Institute for Risk Assessment
ORCID0000-0003-0969-1533
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2021
H-INDEX0
  • Analysis of German BSE Surveillance Data

    Open Access•Matthias Greiner, Thomas Selhorst et al.•ARTICLE•International Journal of…•2021

    Quantitative risk assessments for Bovine spongiform encephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent (i.e.,…

  • Comparison of Bayesian and frequentist methods for prevalence estimation under misclassification

    Open Access•Matthias Flor, Michael Weiss et al.•ARTICLE•BMC Public Health•2020

    The Bayesian prevalence estimation method should be prefered over traditional frequentist methods. An acceptable alternative is to combine the Rogan-Gladen point estimate with the Lang-Reiczigel confidence interval

No prominent works on this page.

  • Comparison of Bayesian and frequentist methods for prevalence estimation under misclassification

    Open Access•Matthias Flor, Michael Weiss et al.•ARTICLE•BMC Public Health•2020

    The Bayesian prevalence estimation method should be prefered over traditional frequentist methods. An acceptable alternative is to combine the Rogan-Gladen point estimate with the Lang-Reiczigel confidence interval

  • Analysis of German BSE Surveillance Data

    Open Access•Matthias Greiner, Thomas Selhorst et al.•ARTICLE•International Journal of…•2021

    Quantitative risk assessments for Bovine spongiform encephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent (i.e.,…

Confidence interval (2 works) · Credible interval (2 works) · Animal Disease Management and Epidemiology (1 work) · Bayesian inference (1 work) · Bayesian probability (1 work) · Cohort (1 work) · Confidence distribution (1 work) · Coverage probability (1 work) · Demography (1 work) · Demography (1 work)

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