Before fitting a model, the Fit Curve report contains only a plot of Y versus X. After fitting a model, the fitted model is added to the plot (when no grouping variable is specified on the platform launch window). The report contains the following results:
To create the report shown in Model Comparison Report, select Sigmoid Curves > Logistic Curves > Fit Logistic 4P and Sigmoid Curves > Fit Gompertz 4P from the Fit Curve red triangle menu.
Gives a measure of the goodness of fit of an estimated statistical model that can be used to compare two or more models. AICc is a modification of the AIC adjusted for small samples. AICc can only be computed when the number of data points is at least two greater than the number of parameters. The model with the lowest AICc value is the best, which is the Logistic 4P in our example. See Likelihood, AICc, and BIC in the Fitting Linear Models book.
Gives a measure based on the likelihood function of model fit that is helpful when comparing different models. The model with the lower BIC value is the better fit. See Likelihood, AICc, and BIC in the Fitting Linear Models book.
The Model Comparison platform provides additional options, such as plotting residual and actual values. See the Model Comparison topic for more information.
Gives plots of the data with the fitted model. See Initial Model Reports for Logistic 4P Model. The plots are shown only when you select a Grouping variable on the platform launch window.
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. For details, see Test Parallelism.
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. For details, see Compare Parameter Estimates.
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. For details, see Equivalence Test.
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 the Profilers book.
Predicts an X value for a specific Y value. For more information about inverse prediction, see Inverse Prediction in the Fitting Linear Models book.