Traditional High-Resolution Graphics |
This section provides examples of using syntax available with the traditional high-resolution plots. A more modern alternative is to use ODS Graphics. See the section ODS Graphics for details.
There are four plot statements that you can use to request traditional high-resolution plots: CDFPLOT, IPPPLOT, LPREDPLOT, and PREDPPLOT. Some of these statements apply only to either the binomial model or the multinomial model. Table 74.33 shows the availability of these statements for different models.
Statement |
Binomial |
Multinomial |
|
CDFPLOT |
No |
Yes |
|
IPPPLOT |
Yes |
No |
|
LPREDPLOT |
Yes |
Yes |
|
PREDPPLOT |
Yes |
Yes |
The following example uses the data set study in the section Estimating the Natural Response Threshold Parameter to illustrate how to create high-resolution plots for the binomial model:
proc probit data=study log10 optc; model respond/number=dose; predpplot var=dose cfit=blue; inset; lpredplot var=dose cfit=blue; inset; ippplot var=dose cfit=blue; inset/pos=se; run;
All plot statements must follow the MODEL statement. The VAR= option specifies a continuous independent variable (dose variable) against which the predicted probability or the linear predictor is plotted. The INSET statement requests the inset box with summary information. See the section INSET Statement for more details.
The PREDPPLOT statement creates a plot that shows the relationship between dosage level, observed response proportions, and estimated probability values. See the section PREDPPLOT Statement for more details. The IPPPLOT statement creates a similar plot. See the section IPPPLOT Statement for details about this plot. The LPREDPLOT statement creates a linear predictor plot, which is described in the section LPREDPLOT Statement.
The following example uses the data set multi from Example 74.2 to illustrate how to create high-resolution plots for the multinomial model:
proc probit data=multi order=data; class prep symptoms; model symptoms=prep ldose; cdfplot var=ldose level=("None" "Mild" "Severe") cfit=blue cframe=ligr noconf; lpredplot var=ldose level=("None" "Mild" "Severe") cfit=blue cframe=ligr; predpplot var=ldose level=("None" "Mild" "Severe") cfit=blue cframe=ligr; weight n; run;
The CDFPLOT statement creates a plot that shows the relationship between the cumulative response probabilities and the dose levels. The multinomial model plots are similar to those with the binomial model.