simData2s {eggCounts} R Documentation

## Simulate faecal egg count data (2-sample situation)

### Description

Generates two samples of (zero-inflated) egg count data

### Usage

simData2s(n = 10, preMean = 500, delta = 0.1, kappa = 0.5,
deltaShape = NULL, phiPre = 1, phiPost = phiPre, f = 50,
paired = TRUE, rounding = TRUE, seed = NULL)


### Arguments

 n positive integer. Sample size. preMean numeric. True pre-treatment epg. delta numeric. Proportion of epg left after treatment, between 0 and 1. 1 - \delta is reduction in mean after treatment, delta = 0.1 indicates a 90% reduction. kappa numeric. Overdispersion parameter, \kappa \to \infty corresponds to Poisson distribution. deltaShape numeric. Shape parameter for the distribution of reductions. If NULL, the same reduction is applied to the latent true epg of each animal. phiPre numeric. Pre-treatment prevalence (i.e. proportion of infected animals), between 0 and 1. phiPost numeric. Post-treatment prevalence, between 0 and 1. f integer or vector of integers. Correction factor of the egg counting technique paired logical. If TRUE, paired samples are simulated. Otherwise unpaired samples are simulated. rounding logical. If TRUE, the Poisson mean for the raw counts is rounded. The rounding applies since the mean epg is frequently reported as an integer value. For more information, see Details. seed an integer that will be used in a call to set.seed before simulation. If NULL, a random seed is allocated.

### Details

In the simulation of raw (master) counts, it follows a Poisson distribution with some mean. The mean is frequently rounded down if it has a very low value and rounding = TRUE, there expects to be some bias in the mean reduction when \mu < 150 and \delta < 0.1. Set rounding = FALSE for not to have any bias.

### Value

A data.frame with six columns, namely the observed epg (obs), actual number of eggs counted (master) and true epg in the sample (true) for both pre- and post- treatment.

### Author(s)

Craig Wang
Michaela Paul

fecr_stan for analyzing faecal egg count data with two samples

### Examples

fec <- simData2s(n = 10, preMean = 500, delta = 0.1, kappa = 0.5)

## show the bias when the true reduction should be 95%
fec <- simData2s(n = 1e5, preMean = 150, delta = 0.05,
kappa = 0.5, seed = 1)
1 - mean(fec$masterPost)/mean(fec$masterPre)
## without bias
fec <- simData2s(n = 1e5, preMean = 150, delta = 0.05,
kappa = 0.5, seed = 1, rounding = FALSE)
1 - mean(fec$masterPost)/mean(fec$masterPre)


[Package eggCounts version 2.3-2 Index]