Shared Concepts and Topics

Syntax: EFFECTPLOT Statement

  • EFFECTPLOT <plot-type <(plot-definition-options)>> </ options>;

The available plot-types and their plot-definition-options are described in Table 15. Table 17 lists the options that can be specified after a slash (/) for any plot-type, and Table 18 lists additional options that enhance specific plot-types. Full descriptions of the plot-definition-options and the other options are provided in the section Dictionary of Options.

Table 15: Plot-Types and Plot-Definition-Options

Plot-Type and Description Plot-Definition-Options
BOX
Displays a box plot of continuous response data at each level of a CLASS effect, with predicted values superimposed and connected by a line. This is an alternative to the INTERACTION plot-type. PLOTBY= variable or CLASS effect
X= CLASS variable or effect
CONTOUR
Displays a contour plot of predicted values against two continuous covariates. PLOTBY= variable or CLASS effect
X= continuous variable
Y= continuous variable
FIT
Displays a curve of predicted values versus a continuous variable. PLOTBY= variable or CLASS effect
X= continuous variable
INTERACTION
Displays a plot of predicted values (possibly with error bars) versus the levels of a CLASS effect. The predicted values are connected with lines and can be grouped by the levels of another CLASS effect. PLOTBY= variable or CLASS effect
SLICEBY= variable or CLASS effect
X= CLASS variable or effect
MOSAIC
Displays a mosaic plot of predicted values using up to three CLASS effects. PLOTBY= variable or CLASS effect
X= CLASS effects
SLICEFIT
Displays a curve of predicted values versus a continuous variable grouped by the levels of a CLASS effect. PLOTBY= variable or CLASS effect
SLICEBY= variable or CLASS effect
X= continuous variable


By default, a single plot is produced based on the type of response variable and the number of continuous and classification covariates in the model, as shown in Table 16. If you have a polytomous response model, then the response variable is treated as the grouping classification variable in this table. If your model does not fit into Table 16, then a default plot is not produced; however, specifying the plot-type argument displays a plot with the extra continuous covariates fixed at their mean values and the extra classification covariates fixed at their reference levels.

Table 16: Default Plot-Types

Number of Covariates Type of Response Variable
Classification Continuous Continuous or Binary Polytomous
1 0 INTERACTION INTERACTION with groups
2 0 INTERACTION with groups None
2 0 INTERACTION with nested covariate None
0 1 FIT SLICEFIT
0 2 CONTOUR None
1 1 SLICEFIT None


Table 17 and Table 18 list the options that can be specified after a slash (/) to enhance the effect plots.

Table 17: Available Options for All Plot-Types

AT<args> ILINK NOOFFSET NROWS=Superscript a b PREDLABEL=
ATLEN= INDIVIDUALSuperscript a NCOLS=Superscript a b OBS<(options)> UNPACK
ATORDER= LINKSuperscript b NOOBSSuperscript a b PLOTBYLEN=
Superscript a Not available for the BOX plot-type.
Superscript b Not available for the MOSAIC plot-type.


Note: If your model contains an offset variable and the NOOFFSET option is not specified or not valid, then the predicted values are computed only at the observations. In this case, the FIT and SLICEFIT plot-types display scatter plots of the predicted values, the CONTOUR plot-type displays the residuals against two continuous covariates but with no fitted surface, the INTERACTION plot-type does not connect the predicted values with lines, and the BOX plot-type is unchanged.


Last updated: December 09, 2022