toxtestD (version 2.0)

doseD: doseD: Construction of an individual dose scheme

Description

This function calculates optimal concentration points according to the EC target specification, spontaneous lethality (SL), immunity (IY) and the accepted type I and type II error levels.

Usage

doseD(DP, immunity.p = 0, SL.p = 0, target.EC.p = 10,  nconc = 8, text = TRUE, risk.type = 2,  print.result = "03.dosestrategy.txt")

Arguments

DP

The results from pretests should be given as a data.frame with the columns "name", "organisms", "death", "concentration" and "unit", which will be needed for the calculations of the dose scheme

immunity.p

Immunity in percent (see also explanation in "spoD")

SL.p

Spontaneous level in percent, calculated from the users experimental data by the function "spoD"

target.EC.p

Effect of special interest in percent. More than one target may be given for one calculation. Example: if EC5 and EC10 are of special interest, then use target.EC=c(5,10). Corresponding dose points will be allocated around both targets with distances derived from the confidence interval width.

nconc

Number of different concentrations the user is willing to test in the experiment.

text

text=TRUE adds extended information in the plot.

risk.type

Choose one of (1,2,3) to select a risk type (see reference for more detail): 1: Total risk (TR): The total risk is the total response expressed as percentage of affected biological units among all treated units. Spontaneous lethality and immunity are ignored.

2: Added risk (AR): The reference frame is restricted below and above by spontaneous lethality (SL) and immunity (IY). Only the response above the SL is considered as an effect. Using AR, the total response associated with a target effect of size xx and a spontaneous lethality SL is xx + SL.

3: Extra risk (ER): The reference frame is the interval from SL to (100%-IY). Using ER, the total response associated with a target effect of size xx is SL + 0.01 * xx * (100%-SL-IY).

print.result

If empty, the result is written to "03.dosestrategy.txt" in the calling directory, if a file name is given, the result is written to that file, if FALSE, nothing is written

Value

nconc rows and contains columns c("concentration","unit","effect") describing the concentrations in units "unit" for the effect in "effect".

References

Optimal test design for binary response data: the example of the Fish Embryo Toxicity Test. Submitted.

Examples

 # calculation of an optimal dose scheme
 #  pretest results as dataframe (DP)
  DP <- data.frame(   name=c("neg.control",rep("substance",times=6)),
                      organisms=c(42,41,42,42,38,42,39),
                      death= c(1,3,40,20,12,40,13),
                      concentration=c(0.0,2.0,3.5,4.0,6.0,8.0,6.0),
                      unit=rep("mg/ml",times=7)  )
 # test design
 doseD(DP=DP,immunity.p=4.7,SL.p=9,target.EC.p=c(15,30,40),
       nconc=9,text=TRUE,risk.type=1)
 doseD(DP=DP,immunity.p=4.7,SL.p=9,target.EC.p=c(15,30,40),
       nconc=9,text=TRUE,risk.type=2)
 doseD(DP=DP,immunity.p=4.7,SL.p=9,target.EC.p=c(15,30,40),
       nconc=9,text=TRUE,risk.type=3)
 doseD(DP=DP,immunity.p=4.7,SL.p=9,target.EC.p=c(15,30,40),
       nconc=9,text=TRUE,risk.type=3,print.result="doseD4.txt")
 doseD(DP=DP,immunity.p=4.7,SL.p=9,target.EC.p=c(15,30,40),
       nconc=9,text=TRUE,risk.type=3,print.result=FALSE)