Stat > Regression > Binary Logistic Regression > Fit Binary Logistic Model > Graphs
Receiver operating characteristic (ROC)
curve
Display the receiver operating characteristic (ROC) curve. A footnote on the plot gives the area under the ROC curve. You can use the area under the ROC curve to compare models. The ROC curve plots the true positive rate (TPR) against the false positive rate (FPR).
Use residual plots to examine whether your model meets the assumptions of regression and ANOVA. For more information, go to Residual plots in Minitab.
Individual plots: Select the residual plots that you want to display.
Histogram
of residuals
Display a histogram of the residuals.
Normal probability plot of residuals
Display a normal probability plot of the residuals.
Residuals versus fits
Display the residuals versus the fitted values. This plot is not available when the data are in the binary format or the frequency format because the resulting pattern would not be informative.
Residuals versus order
Display the residuals versus the order of the data. The row number for each data point is shown on the x-axis.
Three in one or Four in one: Display the residual plots together in one graph. If the data are in the binary format or the frequency format, the layout has a histogram of residuals, a normal probability plot of residuals, and a plot of residuals versus order. If the data are in the event/trial format, the layout also has a plot of residuals versus the fits on the link scale.
Residuals versus the
variables
Enter one or more variables to plot versus the residuals. You can plot the following types of variables:
Variables that are already in the current model, to look for curvature in the residuals.
Important variables that are not in the current model, to determine whether they are related to the response.
