Provides tools for the analysis of survival/reproduction
toxicity test data in quantitative environmental risk assessment. It can be
used to explore/visualize experimental data, and to get estimates
of \(LC_{x}\) (\(X\)% Lethal Concentration) or,
\(EC_{x}\) (\(X\)% Effective Concentration) by fitting exposure-response
curves. The \(LC_{x}\), \(EC_{x}\) and parameters of the curve are
provided along with an indication of the uncertainty of the estimation.
morse can also be used to get an estimation of the \(NEC\) (No Effect Concentration)
by fitting a Toxico-Kinetic Toxico-Dynamic (TKTD) model (GUTS: General Unified Threshold
model of Survival). Within the TKTD-GUTS approach, \(LC(x,t)\), \(EC(x,t)\) and \(MF(x,t)\)
(\(x\)% Multiplication Factors aka Lethal Profiles) can be explored in proportion \(x\) and
time \(t\).
Virgile Baudrot <virgile.baudrot@posteo.net>, Sandrine Charles <sandrine.charles@univ-lyon1.fr>, Marie Laure Delignette-Muller <marielaure.delignettemuller@vetagro-sup.fr>, Wandrille Duchemin <wandrille.duchemin@insa-lyon.fr>, Benoit Goussen <Benoit.Goussen@ibacon.com>, Guillaume Kon-Kam-king <guillaume.kon-kam-king@univ-lyon1.fr>, Christelle Lopes <christelle.lopes@univ-lyon1.fr>, Philippe Ruiz <philippe.ruiz@univ-lyon1.fr>, Alexander Singer, <Alexander.Singer@rifcon.de> Philippe Veber <philippe.veber@univ-lyon1.fr>
Maintainer: Philippe Veber <philippe.veber@univ-lyon1.fr>
Estimation procedures in morse can be used without a deep knowledge of
their underlying probabilistic model or inference methods. Rather, they
were designed to behave as well as possible without requiring a user to
provide values for some obscure parameters. That said, morse models can also
be used as a first step to tailor new models for more specific situations.
The package currently handles survival and reproduction data. Functions
dedicated to survival (resp. reproduction) analysis start with a
surv (resp. repro) prefix. morse provides a similar
workflow in both cases:
create and validate a data set
explore a data set
plot a data set
fit a model on a data set and output the expected estimates
check goodness of fit with posterior preditive check plot (ppc)
More specifically, for survival data handles with TKTD `GUTS` model, morse
provides:
plot \(LC(x,t)\) and \(MF(x,t)\).
compute goodness-of-fit measures (PPC percent, NRMSE and SPPE)
Those steps are presented in more details in the "Tutorial" vignette, while
a more formal description of the estimation procedures are provided in the
vignette called "Models in morse package". Please refer to these documents
for further introduction to the use of morse.
This reference manual is a detailed description of the functions exposed in the package.
Getting started The package uses the rjags package
(Plummer, 2013), an R interface to the JAGS library for Bayesian model
estimation. Note that the rjags package does not include a copy
of the JAGS library: you need to install it separately. For instructions
on downloading JAGS, see the home page at
https://mcmc-jags.sourceforge.io. Once done, simply follow the steps
described in the tutorial vignette.
| Package: | morse |
| Type: | Package |
| Version: | 3.2.0 |
| Date: | 2018-11-15 |
| License: | GPL (>=2) |
Delignette-Muller, M.L., Ruiz P. and Veber P. (2017) Robust fit of toxicokinetic-toxicodynamic models using prior knowledge contained in the design of survival toxicity tests.
Delignette-Muller, M.L., Lopes, C., Veber, P. and Charles, S. (2014) Statistical handling of reproduction data for exposure-response modelling.
Forfait-Dubuc, C., Charles, S., Billoir, E. and Delignette-Muller, M.L. (2012) Survival data analyses in ecotoxicology: critical effect concentrations, methods and models. What should we use?
Plummer, M. (2013) JAGS Version 4.0.0 user manual. https://sourceforge.net/projects/mcmc-jags/files/Manuals/4.x/jags_user_manual.pdf/download
Baudrot, V., Preux, S., Ducrot, V., Pavé, A. and Charles, S. (2018) New insights to compare and choose TKTD models for survival based on an inter-laboratory study for Lymnaea stagnalis exposed to Cd.
EFSA PPR Scientific Opinion (2018) Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms https://www.efsa.europa.eu/en/efsajournal/pub/5377.
rjags,
ggplot2