A set of functions to allow analysis of count data (such as faecal egg count data) using Bayesian MCMC methods. Returns information on the possible values for mean count, coefficient of variation and zero inflation (true prevalence) present in the data. A complete faecal egg count reduction test (FECRT) model is implemented, which returns inference on the true efficacy of the drug from the pre- and post-treatment data provided, using non-parametric bootstrapping as well as using Bayesian MCMC. Functions to perform power analyses for faecal egg counts (including FECRT) are also provided.
|Author||Matthew Denwood [aut, cre]|
|Date of publication||2015-04-20 11:46:52|
|Maintainer||Matthew Denwood <firstname.lastname@example.org>|
bayescount: Analyse Count data using MCMC
bayescount.single: Analyse Count data using MCMC
fec.power: Count Data Power Analysis Calculations
fec.power.limits: Count Data Predicted Precision Calculations
fecrt.analysis: Analyse FECRT Data Using MCMC to Give a Probability...
fecrt.model: Create an MCMC model to analyse FECRT Data
fecrt.power: FECRT Power Analysis Calculations
fecrt.power.limits: FECRT Predicted Precision Calculations
likelihood: Calculate the (Log) Likelihood of Obtaining Data from a...
lnormal.params: Calculate the Log-Normal Mean and Standard Deviation Using...
maximise.likelihood: Calculate the Maximum Likelihood Parameters of a Continuous...
normal.params: Calculate the Normal Mean and Standard Deviation Using the...
run.model: Analyse Count Data Using Jags