simData2s: Simulate faecal egg count data (2-sample situation)

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/simData.R

Description

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

Usage

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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

sample size (number of animals)

preMean

true pre-treatment epg

delta

proportion of epg left after treatment, between 0 and 1. 1 - δ is reduction in mean after treatment, delta = 0.1 indicates a 90% reduction

kappa

overdispersion parameter, κ -> ∞ corresponds to Poisson distribution

deltaShape

shape parameter for the distribution of reductions. If NULL, the same reduction is applied to the latent true epg of each animal.

phiPre

pre-treatment prevalence (i.e. proportion of infected animals), between 0 and 1

phiPost

post-treatment prevalence, between 0 and 1

f

correction factor of the egg counting technique, either an integer or a vector of integers with length n

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, please 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 a up to 3-10% positive bias in the mean reduction when μ < 150 and δ < 0.1. Set rounding = FALSE if one does not wish to have any bias.

Value

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

Author(s)

Craig Wang
Michaela Paul

See Also

fecr_stan for analyzing faecal egg count data with two samples

Examples

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

## show the positive bias when the true reduction should be 95%
set.seed(1)
fec <- simData2s(n=1e5, preMean=150, delta=0.05, kappa=0.5)
1-mean(fec$masterPost)/mean(fec$masterPre)

eggCounts documentation built on May 2, 2018, 5:06 p.m.