Predict X% Lethal Concentration at the maximum time point (default).
Predict median and 95% credible interval of the x% Lethal Concentration.
The function LCx, x% Lethal Concentration (LC_x), is use to compute
the dose required to kill x% of the members of a tested population
after a specified test duration (time_LCx) (default is the maximum
time point of the experiment).
Mathematical definition of x% Lethal Concentration at time t, denoted LC(x,t), is:
S(LC(x,t), t) = S(0, t)*(1- x/100),
where S(LC(x,t), t) is the survival probability at concentration LC(x,t) at time t, and S(0,t) is the survival probability at no concentration (i.e. concentration is 0) at time t which reflect the background mortality h_b:
S(0, t) = exp(-hb* t).
In the function LCx, we use the median of S(0,t) to rescale the
x% Lethal Concentration at time t.
LCx(object, ...) ## S3 method for class 'survFit' LCx(object, X, time_LCx = NULL, conc_range = NULL, npoints = 100, ...)
object |
An object of class |
... |
Further arguments to be passed to generic methods |
X |
Percentage of individuals dying (e.g., 50 for LC_{50}, 10 for LC_{10}, ...) |
time_LCx |
A number giving the time at which LC_{x} has to be estimated. If NULL, the latest time point of the experiment is used. |
conc_range |
A vector of length 2 with minimal and maximal value of the range of concentration. If NULL, the range is define between 0 and the highest tested concentration of the experiment. |
npoints |
Number of time point in |
When class of object is survFit, see LCx.survFit.
The function returns an object of class LCx, which is a list
with the following information:
X_prop |
Survival probability of individuals surviving considering the median of the background mortality (i.e. S(0, t)*(1- x/100)) |
X_prop_provided |
Survival probability of individuals surviving as provided in arguments (i.e. (100-X)/100) |
time_LCx |
A number giving the time at which LC_{x} has to be estimated as provided in arguments or if NULL, the latest time point of the experiment is used. |
df_LCx |
A |
df_dose |
A |
# (1) Load the data
data("propiconazole")
# (2) Create an object of class 'survData'
dataset <- survData(propiconazole)
## Not run:
# (3) Run the survFit function with model_type SD (or IT)
out_SD <- survFit(dataset, model_type = "SD")
# (4) estimate LC50 at time 4
LCx(out_SD, X = 50, time_LCx = 4)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.