bayescount (version 0.9.99-4)

fecrt.model: Create an MCMC model to analyse FECRT Data

Description

This function generates and compiles a JAGS model representation of a faecal egg count reduction test (FECRT) analysis. The return value can be updated manually using extend.jags

Usage

fecrt.model(data, paired.model = FALSE, fix.controls = FALSE,
  fix.efficacy = TRUE, fix.variation = TRUE, zero.inflation = FALSE,
  effect.prior = "dbeta(1,1)", mean.prior = "dmouch(1)",
  precision.prior = "dmouch(1)", ...)

Value

Returns an object of class runjags-class

Details

Pre-treatment data are assumed to arise from either a gamma-Poisson or zero-inflated gamma-Poisson distribution, with post-treatment data described by a separate gamma-Poisson or zero-inflated gamma-Poisson distribution. The change in mean between these distributions is therefore the mean egg count reduction. A change in shape parameter of the gamma distribution is also permitted if fix.variation=FALSE. If paired.model=TRUE, a slightly different formulation is used whereby the observed count pre-treatment is assumed to follow a compound gamma-gamma-Poisson distribution with the variability within and between animals separated. The post treatment mean for each animal is derived from the pre-treatment animal mean and FEC reduction. This formulation allows data with non-random missing post-treatment counts to be analysed correctly, and also allows data with repeat counts from an individual to be analysed - providing a method of increasing the power of the method substantially. The fix.efficacy=FALSE option is only permitted for the paired.model=TRUE option, and allows the reduction estimated to vary between individuals. Problems with convergence are likely to be encountered with this option unless there is a substantial amount of replicate data avaialble within individuals.

References

M. J. Denwood, S. W. J. Reid, S. Love, M. K. Nielsen, L. Matthews, I. J. McKendrick, and G. T. Innocent. Comparison of three alternative methods for analysis of equine Faecal Egg Count Reduction Test data. Prev. Vet. Med. (2009), doi:10.1016/j.prevetmed.2009.11.009

See Also

fecrt.analysis for comparisons of fitted MCMC models to bootstrapping results

Examples

# Data in an appropriate format:
data <- data.frame(Count=rpois(80,rep(c(10,10,2,2), 20)),
Subject=rep(1:20, each=4), Time=rep(rep(1:2,each=2),40),
Sample=1:2, Control=rep(c(0,1), each=40))
# Compile the model - a paired model is required because
# there are replicate samples within an individual:
model <- fecrt.model(data, paired.model=TRUE)
# Update the model - requires runjags:
library('runjags')
results <- extend.jags(model, burnin=5000)