ODS Graphics

Statistical procedures use ODS Graphics to create graphs as part of their output. ODS Graphics is described in detail in Chapter 21, Statistical Graphics Using ODS.

Before you create graphs, ODS Graphics must be enabled (for example, with the ODS GRAPHICS ON statement). For more information about enabling and disabling ODS Graphics, see the section Enabling and Disabling ODS Graphics in Chapter 21, Statistical Graphics Using ODS.

The overall appearance of graphs is controlled by ODS styles. Styles and other aspects of using ODS Graphics are discussed in the section A Primer on ODS Statistical Graphics in Chapter 21, Statistical Graphics Using ODS.

When ODS Graphics is enabled, by default the PLS procedure produces a plot of the variation accounted for by each extracted factor, as well as a correlation loading plot for the first two extracted factors (if the final model has at least two factors). The plot of the variation accounted for can take several forms:

• If the PLS analysis does not include cross validation, then the plot shows the total R square for both model effects and the dependent variables against the number of factors.

• If you specify the CV= option to select the number of factors in the final model by cross validation, then the plot shows the R-square analysis discussed previously as well as the root mean PRESS from the cross validation analysis, with the selected number of factors identified by a vertical line.

The correlation loading plot for the first two factors summarizes many aspects of the two most significant dimensions of the model. It consists of overlaid scatter plots of the scores of the first two factors, the loadings of the model effects, and the loadings of the dependent variables. The loadings are scaled so that the amount of variation in the variables that is explained by the model is proportional to the distance from the origin; circles indicating various levels of explained variation are also overlaid on the correlation loading plot. Also, the correlation between the model approximations for any two variables is proportional to the length of the projection of the point corresponding to one variable on a line through the origin passing through the point corresponding to the other variable; the sign of the correlation corresponds to which side of the origin the projected point falls on.

The R square and the first two correlation loadings are plotted by default when ODS Graphics is enabled, but you can produce many other plots for the PROC PLS analysis.

### ODS Graph Names

PROC PLS assigns a name to each graph it creates using ODS. You can use these names to reference the graphs when using ODS. The names are listed in Table 69.3.

Table 69.3 Graphs Produced by PROC GLM

ODS Graph Name

Plot Description

Option

CVPlot

Cross validation and R-square analysis (default, as appropriate)

DModXPlot

Distance of each observation to the X model

PLOT=DMODX

DModXYPlot

Distance of each observation to the X and Y models

PLOT=DMODXY

DModYPlot

Distance of each observation to the Y model

PLOT=DMODY

DiagnosticsPanel

Panel of diagnostic plots for the fit

PLOT=DIAGNOSTICS

AbsResidualByPredicted

Absolute residual by predicted values

PLOT=DIAGNOSTICS(UNPACK)

ObservedByPredicted

Observed by predicted

PLOT=DIAGNOSTICS(UNPACK)

QQPlot

Residual Q-Q plot

PLOT=DIAGNOSTICS(UNPACK)

ResidualByPredicted

Residual by predicted values

PLOT=DIAGNOSTICS(UNPACK)

ResidualHistogram

Residual histogram

PLOT=DIAGNOSTICS(UNPACK)

RFPlot

RF plot

PLOT=DIAGNOSTICS(UNPACK)

ParmProfiles

Profiles of regression coefficients

PLOT=PARMPROFILES

R2Plot

R-square analysis (default, as appropriate)

ResidualPlots

Residuals for each dependent variable

PLOT=RESIDUALS

VariableImportancePlot

Profile of variable importance factors

PLOT=VIP

XScorePlot

Scatter plot matrix of X-scores against each other

PLOT=XSCORES

XWeightPlot

Scatter plot matrix of X-weights against each other

PLOT=XWEIGHTPLOT

XWeightProfiles

Profiles of the X-weights

PLOT=XWEIGHTPROFILES

XYScorePlot

Scatter plot matrix of X-scores against Y-scores

PLOT=XYSCORES

YScorePlot

Scatter plot matrix of Y-scores against each other

PLOT=YSCORES

YWeightPlot

Scatter plot matrix of Y-weights against each other

PLOT=YWEIGHTPLOT