Model Fit Options
Each model report in the Fit Curve platform 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, as well as the Linear Regression model, with the exception of higher-order polynomials. See Test Parallelism.
Inflection Point
(Available only for Weibull Growth, Logistic 4P Rodbard, and Logistic 5P models.) Shows or hides a report that contains the inflection point estimates for the model. The report includes the inflection point estimate, the standard error of the estimate, and the lower and upper confidence intervals for the estimate. If a Group variable is specified in the platform launch window, an estimate is calculated for each group and an ANOM chart that compares the inflection points is included in the report.
Area Under Curve
Gives the area under the fitted curve. This option is available for the following models: One Compartment, Two Compartment, and all Peak Models. 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
(Available only for Cell Growth 4P and One Compartment models.) Calculates the estimate of the regressor, X, at the peak of the fitted curve. The standard error of the estimate is also shown.
Peak Response
(Available for Cell Growth 4P and One Compartment models.) Calculates the estimate of the response, Y, at the peak of the fitted curve. The standard error of the estimate is also shown.
Compare Parameter Estimates
(Available only when a Group variable is specified on the platform launch window.) Gives an analysis for testing the equality of parameters across levels of the grouping variable. See Compare Parameter Estimates.
Equivalence Test
(Available only when a Group variable is specified on the platform launch window.) Gives an analysis for testing the equivalence of models across levels of the grouping variable. See Equivalence Test.
Curve DOE Analysis
(Available only if a grouping variable and at least one supplementary variable are specified in the launch window. The grouping variable must contain at least five levels. Not available if the Columns as Functions tab is used.) 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 Best Subset. If the number of terms in the model is greater than 20 or the number of functions is greater than 1000, the Estimation Method automatically switches to Pruned Forward. If the data table is from a Definitive Screening Design, the Estimation Method automatically switches to Two Stage Forward Selection. Alternatively, you can specify a model script in the original data table that defines the desired model fit. The 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 about 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 Fit Plot
Shows or hides a plot of the fitted values. If a Group variable is specified, there is also a grid of plots of the fitted values for each level of the Group 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 a new formula column to the original data table. The new column contains the prediction formula for the response.
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. If you use either of the Rows as Functions or Columns as Functions tabs in the launch window, the Save Stacked Data option is the only save option available.
Save Prediction Formula
Saves a new formula column to the original data table. The new column contains the prediction formula for the current parameter estimates.
Save Std Error of Predicted
Saves a new formula column to the original data table. The new column contains the formula to calculate the standard errors of the predicted values.
Save Parametric Prediction Formula
Saves a new formula column to the original data table. The new column contains the prediction equation in parametric form.
Tip: The Save Parametric Prediction Formula option is helpful if you want to use the fitted model in the custom Nonlinear platform.
Save Residual Formula
Saves a new formula column to the original data table. The new column contains a formula for the residuals.
Save Studentized Residual Formula
Saves a new formula column to the original data table. The new column contains the formula for the studentized residuals, which are standard residuals divided by their estimated standard deviations.
Save First Derivative
Saves a new formula column to the original data table. The new column contains the formula for the first derivative of the prediction function with respect to the X variable.
Save Std Error of First Derivative
Saves a new column to the original data table. The new column contains the formula for the standard error of the first derivative of the prediction.
Save Inverse Prediction Formula
Saves a new formula column to the original data table. The new column contains the formula for the inverse function of the fitted model. The inverse function is the equation for predicting the X variable given the Y variable.
Save Stacked Data
Saves columns to a new data table. The data table contains the original data in the stacked format as well as a column for the predicted values of the response and a column for the residuals.
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.