morse: survFitTT.survDataCstExp – R documentation

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survFitTT.survDataCstExp

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)

## Not run: 
# (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)

## End(Not run)

morse

Modelling Tools for Reproduction and Survival Data in Ecotoxicology

v3.3.1

GPL (>= 2)

Authors

Virgile Baudrot [aut], Sandrine Charles [aut], Marie Laure Delignette-Muller [aut], Wandrille Duchemin [ctb], Benoit Goussen [ctb], Nils Kehrein [ctb], Guillaume Kon-Kam-King [ctb], Christelle Lopes [ctb], Philippe Ruiz [aut], Alexander Singer [ctb], Philippe Veber [aut]

Initial release