Dear Colleagues,

PriorGen is an R package that generates priors in the form of beta and Gamma distributions got proportions. You may find it useful for the generation of priors on the sensitivity/specificity of diagnostic tests and the prevalence of disease.

The findbeta function estimates the parameters of a Beta distribution based on the existing prior beliefs about the mean (or the median or the mode) and whether it is lower or greater that a certain value with a pre-specified certainty (usually set at 95%).

The findbetaqq function estimates the parameters of a Beta distribution based on the existing prior beliefs about the values of two distinct percentiles.

The findbetamupsi function estimates:

  1.  the parameters of a Beta distribution for the expected mean of a proportion -usually the prevalence of disease/infection.
  2.  the parameters of a Gamma distribution expressing our prior belief about the variability (ψ) of the prevalence estimates across the units of the area/region under consideration.

You may download it from here: https://cran.r-project.org/package=PriorGen

Hope you find it helpful and, of course, any comments/suggestions are most welcome.

Polychronis


To cite package ‘PriorGen’ in publications use:

  Polychronis Kostoulas (2018). PriorGen: Generates Prior Distributions
  for Proportions. R package version 1.1.2.
  https://CRAN.R-project.org/package=PriorGen

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {PriorGen: Generates Prior Distributions for Proportions},
    author = {Polychronis Kostoulas},
    year = {2018},
    note = {R package version 1.1.2},
    url = {https://CRAN.R-project.org/package=PriorGen},
  }

Polychronis P. Kostoulas
D.V.M., Ph.D., Assistant Professor
Associate Editor of Preventive Veterinary Medicine
Erasmus+ Departmental Coordinator
Laboratory of Epidemiology, Biostatistics and Animal Health Economics
Faculty of Veterinary Medicine
University of Thessaly
Karditsa, 224 Trikalon st.
GREECE. P.C. 43100
Telephone: +30 2441066022
Mobile: +30 6977881857
Email: [log in to unmask] 
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