Publication date: 11/29/2021

Each model report contains a red triangle menu with some or all of the following options:

Test Parallelism

Helps determine whether the curves are similar in shape when they are shifted along the X axis. In certain situations, it is important to establish parallelism before making further comparisons between groups. This option is available only when a Group variable is specified on the platform launch window. This option is available for the Sigmoid models (Logistic and Gompertz), as well as the Linear Regression model, with the exception of higher-order polynomials. See Test Parallelism.

Area Under Curve

Gives the area under the fitted curve. This option is available for the following models: One Compartment, Two Compartment, Gaussian Peak, and Lorentzian Peak. This option is also available for Bi-Exponential 4P Models, but only when all parameters are positive. The range of integration depends on the type of model and is specified in the report.

If a Grouping variable is specified on the platform launch window, an Analysis of Means is performed for comparing the estimates across groups. If the result for a group exceeds a decision limit, the result is considered different from the overall mean of AUC.

Time to Peak Response

Displays the estimate of the regressor, X, at the peak of the fitted curve. The standard error of the estimate is also shown. This option is available for Cell Growth 4P and One Compartment models.

Peak Response

Displays the estimate of the response, Y, at the peak of the fitted curve. The standard error of the estimate is also shown. This option is available for Cell Growth 4P and One Compartment models.

Compare Parameter Estimates

Gives an analysis for testing the equality of parameters across levels of the grouping variable. This option is available only when a Group variable is specified on the platform launch window. See Compare Parameter Estimates.

Equivalence Test

Gives an analysis for testing the equivalence of models across levels of the grouping variable. This option is available only when a Group variable is specified on the platform launch window. See Equivalence Test.

Curve DOE Analysis

(Available only if a grouping variable and at least one supplementary variable are specified in the launch window.) Launches a Generalized Regression report within the Fit Curve platform. A generalized regression model is fit to each parameter of the nonlinear model using the supplementary variables as model effects. By default, a two degree factorial model is fit and the Estimation Method is Forward Selection. These models are then combined to create a profiler of the response as a function of the regressor variable and the supplementary variables. You can then use the CDOE Profiler to explore how the supplementary variables affect the response.

The Curve DOE Analysis report contains the following red triangle menu options:

Generalized Regression for Model Parameters

Shows or hides the Generalized Regression reports for each model parameter. For more information on Generalized Regression model reports, see Model Fit Reports in Fitting Linear Models.

Diagnostic Plots

Shows or hides actual by predicted and residual plots for the response variable.

CDOE Profiler

Shows or hides the CDOE Profiler, which enables you to explore how the response changes based on the supplementary variables. For more information about the CDOE Profiler red triangle menu options, see Profiler in Profilers.

Save Prediction Formula

Saves the prediction formula for the response to a new column in the data table.

Make Parameter Table

Saves the parameter estimates, standard errors, and t-ratios in a data table. This option is available only when a Group variable is specified on the platform launch window.

Plot Actual by Predicted

Plots actual Y values on the vertical axis and predicted Y values on the horizontal axis.

Plot Residual by Predicted

Plots the residuals on the vertical axis and the predicted Y values on the horizontal axis.

Profiler

Shows or hides a profiler of the fitted prediction function. The derivatives are derivatives of the prediction function with respect to the X variable. For more information about profilers, see Profiler in Profilers.

Save Formulas

Contains options for saving a variety of formula columns in the data table.

Save Prediction Formula

Saves the prediction equation.

Save Std Error of Predicted

Saves the standard error of the predicted values.

Save Parametric Prediction Formula

Saves the prediction equation in parametric form. This is helpful if you want to use the fitted model in the custom Nonlinear platform.

Save Residual Formula

Saves the residuals.

Save Studentized Residual Formula

Saves the studentized residual formula, a standard residual that is divided by its estimated standard deviation.

Save First Derivative

Saves the derivative of the prediction function with respect to the X variable.

Save Std Error of First Derivative

Saves the equation of the standard error of the first derivative.

Save Inverse Prediction Formula

Saves the equation for predicting X from Y.

Custom Inverse Prediction

Predicts an X value for a specific Y value. For more information about inverse prediction, see Inverse Prediction in Fitting Linear Models.

Remove Fit

Removes the model report, the entry from the Model Comparison report, and the fitted line from the plot.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).