Analysis of Dose-Response Curves
ANOVA for dose-response model fits
Asymptotic regression model
Calculation of backfit values from a fitted dose-response model
Leaf length of barley
The modified baro5 function
The Brain-Cousens hormesis models
Transform-both-sides Box-Cox transformation
The Brain-Cousens hormesis models
Bread and meat for the sandwich
The Cedergreen-Ritz-Streibig model
Calculation of combination index for binary mixtures
Extract Model Coefficients
Comparison of effective dose values
Comparison of parameters
Confidence Intervals for model parameters
The Cedergreen-Ritz-Streibig model
Cedergreen-Ritz-Streibig dose-reponse model for describing hormesis
Fitting dose-response models
Sets control arguments
Estimating effective doses
Comparison of relative potencies between dose-response curves
Exponential decay model
Extract fitted values from model
Fractional polynomial-logistic dose-response models
Gamma dose-response model
Normal and log-normal biphasic dose-response models
Showing starting values used
Display available dose-response models
Mean function for the Gompertz dose-response or growth curve
The derivative of the Gompertz function
Model diagnostics for nonlinear dose-response models
Creating isobolograms
Lack-of-fit test for the mean structure based on cumulated residuals
The two-parameter log-logistic function
The three-parameter log-logistic function
The four-parameter log-logistic function
The five-parameter log-logistic function
The log-logistic function
Log-normal dose-response model
The logistic model
Extracting the log likelihood
Estimation of ED values using model-averaging
Maximum mean response
Fitting binary mixture models
Michaelis-Menten model
Assessing the model fit
Mizon-Richard test for dose-response models
Dose-response model selection
Multistage dose-response model with quadratic terms
Dose-response model for estimation of no effect concentration (NEC).
Neill's lack-of-fit test for dose-response models
Testing if there is a dose effect at all
Plotting fitted dose-response curves
Expected or predicted response
Prediction
Printing key features
Printing summary of non-linear model fits
Simulating a dose-response curve
Extracting residuals from the fitted dose-response model
Searching through a range of initial parameter values to obtain conver...
Simulating ED values under various scenarios
Summarising non-linear model fits
Two-phase dose-response model
Updating and re-fitting a model
Model function for the universal response surface approach (URSA) for ...
Calculating variance-covariance matrix for objects of class 'drc'
The two-parameter Weibull functions
The three-parameter Weibull functions
The four-parameter Weibull functions
Weibull model functions
Calculating yield loss parameters
Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.
Useful links