# rdrm: Simulating a dose-response curve In drc: Analysis of Dose-Response Curves

## Description

Simulation of a dose-response curve with user-specified dose values and error distribution.

## Usage

 ```1 2``` ``` rdrm(nosim, fct, mpar, xerror, xpar = 1, yerror = "rnorm", ypar = c(0, 1), onlyY = FALSE) ```

## Arguments

 `nosim` numeric. The number of simulated curves to be returned. `fct` list. Any built-in function in the package drc or a list with similar components. `mpar` numeric. The model parameters to be supplied to `fct`. `xerror` numeric or character. The distribution for the dose values. `xpar` numeric vector supplying the parameter values defining the distribution for the dose values. If `xerror` is a distribution then remember that the number of dose values also is part of this argument (the first argument). `yerror` numeric or character. The error distribution for the response values. `ypar` numeric vector supplying the parameter values defining the error distribution for the response values. `onlyY` logical. If TRUE then only the response values are returned (useful in simulations). Otherwise both dose values and response values (and for binomial data also the weights) are returned.

## Details

The distribution for the dose values can either be a fixed set of dose values (a numeric vector) used repeatedly for creating all curves or be a distribution specified as a character string resulting in varying dose values from curve to curve.

The error distribution for the response values can be any continuous distribution like `rnorm` or `rgamma`. Alternatively it can be the binomial distribution `rbinom`.

## Value

A list with up to 3 components (depending on the value of the `onlyY` argument).

Christian Ritz

## References

~put references to the literature/web site here ~

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```## Simulating normally distributed dose-response data ## Model fit to simulate from ryegrass.m1 <- drm(rootl~conc, data = ryegrass, fct = LL.4()) ## 10 random dose-response curves based on the model fit sim10a <- rdrm(10, LL.4(), coef(ryegrass.m1), xerror = ryegrass\$conc) sim10a ## Simulating binomial dose-response data ## Model fit to simulate from deguelin.m1 <- drm(r/n~dose, weights=n, data=deguelin, fct=LL.2(), type="binomial") ## 10 random dose-response curves sim10b <- rdrm(10, LL.2(), coef(deguelin.m1), deguelin\$dose, yerror="rbinom", ypar=deguelin\$n) sim10b ```

drc documentation built on May 29, 2017, 11:31 a.m.