Abstract
SUMMARY We propose graphical methods for displaying relevant information on a selected parameter from a normal nonlinear regression model. It is shown that the usual extension of added variable plots from linear to nonlinear regression can fail to reveal important diagnostic information, and that this information can be recovered by using a parameter plot that depends on selected elements of the parameter-effects curvature array.
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