Multivariate Analysis: Canonical Discriminant Analysis

The Plots Tab

You can use the Plots tab to create plots that graphically display results of the analysis. (See FigureĀ 29.10.)

Figure 29.10: The Plots Tab

The Plots Tab

Creating a plot often adds one or more variables to the data table. The following plots are available:

Observed groups

creates a spine plot (a one-dimensional mosaic plot) of the groups for the Y variable.

Observed vs. Predicted groups

creates a mosaic plot of the groups for the Y variable versus the group as classified by a discriminant function. Each observation is placed in the group that minimizes the generalized squared distance between the observation and the group mean.

Classification fit plot

creates a plot that indicates how well each observation is classified by the discriminant function. This plot is shown in FigureĀ 29.11. Observations that are close to two or more group means are selected in the plot.

For each observation, PROC DISCRIM computes posterior probabilities for membership in each group. Let $m_ i$ be the maximum posterior probability for the ith observation. The classification fit plot is a plot of $-\log ( m_ i )$ versus i.

Figure 29.11: A Classification Fit Plot

A Classification Fit Plot

Canonical score plot

creates a plot of the first two canonical variables. (If there is only one canonical variable, then a histogram of that variable is created instead.)

Show group means

displays the mean of each group in the score plot.

Add confidence ellipses for means

displays a confidence ellipse for the mean of each group in the score plot.

Confidence level

specifies the probability level for the confidence ellipse.

Shade plot background by confidence level

specifies that the background of each scatter plot be shaded according to a nested family of confidence ellipses.

Add prediction ellipses

displays a prediction ellipse for the mean of each group in the score plot, assuming multivariate normality within each group.

Prediction level

specifies the probability level for the prediction ellipse.