Assessing the model fit — modelFit • drc

Checking the fit of a dose-response model by means of formal significance tests.

Usage

modelFit(object, test = NULL, method = c("gof", "cum"))

Arguments

object: object of class 'drc'.
test: character string defining the test method to apply.
method: character string specifying the method to be used for assessing the model fit.

Value

An object of class 'anova' which will be displayed in much the same way as an ordinary ANOVA table.

Details

Currently two methods are available. For continuous data the classical lack-of-fit test is applied (Bates and Watts, 1988). The test compares the dose-response model to a more general ANOVA model using an approximate F-test. For quantal data the crude goodness-of-fit test based on Pearson's statistic is used.

None of these tests are very powerful. A significant test result is more alarming than a non-significant one.

References

Bates, D. M. and Watts, D. G. (1988) Nonlinear Regression Analysis and Its Applications, New York: Wiley & Sons (pp. 103–104).

Author

Christian Ritz

Examples

## Comparing the four-parameter log-logistic model
##  to a one-way ANOVA model using an approximate F test
## in other words applying a lack-of-fit test
ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = W1.4())
modelFit(ryegrass.m1)
#> Lack-of-fit test
#> 
#>           ModelDf    RSS Df F value p value
#> ANOVA          17 5.1799                   
#> DRC model      20 6.0242  3  0.9236  0.4506