Obtain the variance-covariance matrix of the parameter estimators of a 4PL model.
This function obtains the variance-covariance matrix of the parameter estimators of a 4PL model. The variance-covariance matrix returned by this function can be used to compute the standard errors and confidence intervals for statistical inference.
## S3 method for class 'dr4pl' vcov(object, ...)
object |
An object of the dr4pl class. |
... |
Other function arguments to be passed to the default 'vcov' function. |
This function obtains the variance-covariance matrix of the parameter estimators of a 4PL model. The Hessian matrix is used to obtain the second order approximation to the sum-of-squares loss function, and then the standard errors are computed as the square roots of the half of the Hessian matrix. Please refer to Subsection 5.2.2 of Seber and Wild (1989).
The variance-covariance matrix of the parameter estimators of a 4PL model whose columns are in the order of the upper asymptote, IC50, slope and lower asymptote from left to right and whose rows are in the same order.
Seber GAF, Wild CJ (1989). Nonlinear regression, Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics. John Wiley \& Sons, Inc., New York. ISBN 0-471-61760-1, doi: 10.1002/0471725315, http://dx.doi.org.libproxy.lib.unc.edu/10.1002/0471725315.
obj.dr4pl <- dr4pl(Response ~ Dose, data = sample_data_1) # Fit a 4PL model to data vcov(obj.dr4pl) # Variance-covariance matrix of the parameters obj.dr4pl <- dr4pl(Response ~ Dose, data = sample_data_2) # Fit a 4PL model to data vcov(obj.dr4pl) # Variance-covariance matrix of the parameters
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