survFitTT.survDataCstExp: Fits a Bayesian concentration-response model for target-time...

In morse: Modelling Reproduction and Survival Data in Ecotoxicology

Fits a Bayesian concentration-response model for target-time survival analysis

Description

This function estimates the parameters of an concentration-response model for target-time survival analysis using Bayesian inference. In this model, the survival rate of individuals at a given time point (called target time) is modeled as a function of the chemical compound concentration. The actual number of surviving individuals is then modeled as a stochastic function of the survival rate. Details of the model are presented in the vignette accompanying the package.

Usage

## S3 method for class 'survDataCstExp'
survFitTT(
  data,
  target.time = NULL,
  lcx = c(5, 10, 20, 50),
  n.chains = 3,
  quiet = FALSE,
  ...
)

Arguments

data	an object of class survData
target.time	the chosen endpoint to evaluate the effect of the chemical compound concentration, by default the last time point available for all concentrations
lcx	desired values of x (in percent) for which to compute LC_x.
n.chains	number of MCMC chains, the minimum required number of chains is 2
quiet	if TRUE, does not print messages and progress bars from JAGS
...	Further arguments to be passed to generic methods

Details

The function returns parameter estimates of the concentration-response model and estimates of the so-called LC_x, that is the concentration of chemical compound required to get an (1 - x/100) survival rate.

Value

The function returns an object of class survFitTT, which is a list with the following information:

estim.LCx	a table of the estimated LC_x along with their 95% credible intervals
estim.par	a table of the estimated parameters (medians) and 95% credible intervals
det.part	the name of the deterministic part of the used model
mcmc	an object of class mcmc.list with the posterior distribution
warnings	a table with warning messages
model	a JAGS model object
parameters	a list of parameter names used in the model
n.chains	an integer value corresponding to the number of chains used for the MCMC computation
n.iter	a list of two indices indicating the beginning and the end of monitored iterations
n.thin	a numerical value corresponding to the thinning interval
jags.data	a list of the data passed to the JAGS model
transformed.data	the survData object passed to the function
dataTT	the dataset with which the parameters are estimated

Examples

# (1) Load the data
data(cadmium1)

# (2) Create an object of class "survData"
dat <- survData(cadmium1)


# (3) Run the survFitTT function with the log-logistic
#     binomial model
out <- survFitTT(dat, lcx = c(5, 10, 15, 20, 30, 50, 80),
                 quiet = TRUE)

morse documentation built on Oct. 29, 2022, 1:14 a.m.