`drfit.Rd`

Fit dose-response relationships to dose-response data and calculate biometric results for (eco)toxicity evaluation

```
drfit(data, startlogED50 = NA, chooseone = TRUE, probit = TRUE, logit = FALSE,
weibull = FALSE, linlogit = FALSE, level = 0.95, linlogitWrong = NA,
allWrong = NA, ps0 = 1, ls0 = 0.5, ws0 = 0.5, b0 = 2, f0 = 0,
showED50 = FALSE,
EDx = NULL, EDx.tolerance = 1e-4)
```

- data
A data frame containing dose-response data. The data frame has to contain at least a factor called “substance”, a numeric vector “dose” with the dose values, a vector called “unit” containing the unit used for the dose and a numeric vector “response” with the response values of the test system normalized between 0 and 1. Such a data frame can be easily obtained if a compliant RODBC data source is available for use in conjunction with the function

`drdata`

.If there is a column called “ok” and it is set to “no fit” in a specific line, then the corresponding data point will be excluded from the fitting procedure, although it will be plotted.

- startlogED50
Especially for the linlogit model, a suitable log10 of the ED50 has to be given by the user, since it is not correctly estimated for data showing hormesis with the default estimation method.

- probit
A boolean defining if cumulative density curves of normal distributions

`pnorm`

are fitted against the decadic logarithm of the dose. Default ist TRUE.- logit
A boolean defining if cumulative density curves of logistic distributions

`plogis`

are fitted to the decadic logarithm of the dose. Default is FALSE.- weibull
A boolean defining if the cumulative density curves of weibull distributions (

`pweibull`

with additionall location parameter and scale=1) are fitted to the decadic logarithm of the dose. Default is FALSE. Note that the weibull distribution is fitted here to the log transformed doses which appears to be an uncommon approach.- linlogit
A boolean defining if the linear-logistic function

`linlogitf`

as defined by van Ewijk and Hoekstra 1993 is fitted to the data. Default is FALSE.- level
The level for the confidence interval listed for the log ED50.

- linlogitWrong
An optional vector containing the names of the substances for which the linlogit function produces a wrong fit.

- allWrong
An optional vector containing the names of the substances for which all functions produce a wrong fit.

- chooseone
If TRUE (default), the models are tried in the order linlogit, probit, logit, weibull, and the first model that produces a valid fit is used. If FALSE, all models that are set to TRUE and that can be fitted will be reported.

- ps0
If the probit model is fitted,

`ps0`

gives the possibility to adjust the starting value for the scale parameter of`pnorm`

.- ls0
If the logit model is fitted,

`ls0`

gives the possibility to adjust the starting value for the scale parameter of`plogis`

.- ws0
If the weibull model is fitted,

`ws0`

gives the possibility to adjust the starting value for the shape parameter of`pweibull`

.- b0,f0
If the linearlogistic model is fitted,

`b0`

and`f0`

give the possibility to adjust the starting values for the parameters b and f.- showED50
If set to TRUE, the ED50 and its confidence interval on the original dose scale (not log scale) is included in the output.

- EDx
A vector of inhibition values x in percent for which the corresponding doses EDx should be reported.

- EDx.tolerance
Tolerance of the effect level, expressed on the response scale from 0 to 1.

A dataframe with the attribute `models`

holding a list of the fitted
dose-response models of class `nls`

. The dataframe has at least
one line for each substance.

For the “linlogit”, “logit” and “probit” models, the
parameter `a`

that is reported coincides with the logED50, i.e the
logED50 is one of the model parameters that is being fitted. Therefore,
a confidence interval for the confidence level `level`

is calculated
using the `confint.nls`

function and listed.

The following variables are in the dataframe:

- Substance
The name of the substance

- ndl
The number of dose levels in the raw data

- n
The total number of data points in the raw data used for the fit

- lld
The decadic logarithm of the lowest dose

- lhd
The total number of data points in the raw data used for the fit

- mtype
If the data did not show a mean response < 0.5 at the highest dose level, the modeltype is set to “inactive”. If the mean response at the lowest dose is smaller than 0.5, the modeltype is set to “active”. In both cases, no fitting procedure is carried out. If the fitted ED50 is higher than the highest dose, “no fit” is given here.

- logED50
The decadic logarithm of the ED50

- low %
The lower bound of the confidence interval of log ED50. The name of the column depends on the requested confidence

`level`

.- high %
The higher bound of the confidence interval of log ED50. The name of the column depends on the requested confidence

`level`

.- unit
The unit used for the dose levels in the dose-response data

- sigma
The square root of the estimated variance of the random error as returned by

`summary.nls`

.- a
For the “linlogit”, “logit” and “probit” models, the parameter

`a`

coincides with the logED50. In the case of the “weibull” model,`a`

is a location parameter.- b
Parameter

`b`

in the case of the “linlogit” fit is the variable b from the`linlogitf`

function. In the case of “probit” fit it is the standard deviation of the fitted normal distribution, in the case of the “logit” fit it is the`scale`

parameter in the`plogis`

function, and in the “weibull” fit it is the`shape`

parameter of the fitted`pweibull`

function.- c
Only the “linlogit” fit produces a third parameter

`c`

which is the variable f from the`linlogitf`

function.

If the parameter `showED50`

was set to TRUE, the ED50 values and their
confidence intervals are also included on the original dose scale.

If one or more response leves were specified in the argument `EDx`

,
the corresponding dose levels are given in addition.

There is a demo for each dataset that can be accessed by
`demo(dataset)`

Further examples are given in help pages to the datasets
`antifoul`

, `IM1xIPC81`

and
`IM1xVibrio`

.
Since version 0.6.1 of this package, there is a drop-in replacement function
`drcfit`

which internally uses the drc package and also gives
confidence intervals for EDx values via this package.

```
data(antifoul)
r <- drfit(antifoul, showED50 = TRUE, EDx = c(5, 10, 20))
#>
#> TBT: Fitting data...
#> Waiting for profiling to be done...
#>
#> Zn Pyrithion: Fitting data...
#> Waiting for profiling to be done...
format(r, digits = 2)
#> Substance ndl n lld lhd mtype logED50 2.5% 97.5% unit sigma a
#> 1 TBT 38 135 -2.7 2.4 probit -0.16 -0.27 -0.056 microM 0.19 -0.16
#> 2 Zn Pyrithion 27 81 -2.1 2.0 probit -0.40 -0.51 -0.292 microM 0.23 -0.40
#> b ED50 ED50 2.5% ED50 97.5% EDx5 EDx10 EDx20
#> 1 0.68 0.68 0.54 0.88 0.053 0.093 0.18
#> 2 0.42 0.40 0.31 0.51 0.082 0.117 0.18
```