The prevalence package allows different ways of specifying the priors and external information used in the true prevalence estimation models. To see how these distributions need to be passed on to the different truePrev
functions, see the documentation for truePrev
, truePrevPools
, truePrevMulti
and truePrevMulti2
.
In general, five distributions are available:
Fixed  This is actually not a (probabilistic) distribution, but just means that you specify a certain parameter as a single, fixed value. In other words, you do not assign any uncertainty to that parameter. 
Uniform  A Uniform distribution gives equal weight or likelihood to each value between a certain minimum and maximum. Values outside of that range get a likelihood of zero. A Uniform(0,1) distribution would mean that each value in between zero and one is equally likely, and is a common uniformative prior for the true prevalence. Find out more on Wikipedia. 
BetaPERT 
A PERT distribution is a synthetic distribution, representing the uncertainty in a parameter defined by a minimum, a maximum, and a most likely value. Function betaPERT can be used to generate the parameters of a PERT distribution from expert opinion on the minimum, maximum, and most likely value.

Beta 
A Beta distribution is characterized by two parameters, denoted alpha and beta (or shape1 and shape2 in R). As it is bounded by (0,1), it is a common distribution for modelling the uncertainty in proportions, such as prevalence, sensitivity and specificity. Find out more on Wikipedia.

BetaExpert 
The betaexpert distribution in the prevalence package provides an alternative way of specifying a Beta distribution. Function betaExpert fits a Beta distribution to expert opinion on a best guess estimate (which can be the mean or the mode), and additional information on a lower bound, an upper bound, or both.

These distributions can be specified in two ways, i.e., using a named list and using socalled BUGSnotation.
Distribution parameters can be specified in a named list()
as follows:
Fixed 
list(dist = "fixed", par) 
Uniform 
list(dist = "uniform", min, max) 
BetaPERT 
See 
Beta 
list(dist = "beta", alpha, beta) 
BetaExpert 
betaExpert for more information on BetaExpert parametrization. 
For Uniform, BetaPERT and Beta distributions, BUGSstyle shorthand notation is also allowed:
Uniform 
~dunif(min, max)

BetaPERT 
~dpert(min, mode, max)

Beta 
~dbeta(alpha, beta)
