SASŪ High-Performance Analytics Samples
The SAS High-Performance Analytics sample programs and install verification tests can be run only after you
edit and submit this file.
The file contains site-specific information about your environment so that the procedures can run successfully.
Example 3 for PROC HPLOGISTIC
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: hploge03 */
/* TITLE: Example 3 for PROC HPLOGISTIC */
/* PRODUCT: HPA */
/* SYSTEM: ALL */
/* KEYS: logistic regression analysis, */
/* polytomous response data */
/* PROCS: HPLOGISTIC */
/* DATA: */
/* */
/* SUPPORT: Bob Derr */
/* REF: SAS/HPA User's Guide, PROC HPLOGISTIC chapter */
/* MISC: */
/* */
/****************************************************************/
/*****************************************************************
Example 3: Ordinal Logistic Regression
*****************************************************************/
/*
The data, taken from McCullagh and Nelder (1989, p.175), were derived from an
experiment concerned with the effect of four cheese additives on taste. The
nine response categories range from strong dislike (1) to excellent taste
(9). Let y be the response variable. The variable Additive specifies the
cheese additive (1, 2, 3, or 4). The data after the DATALINES statement are
arranged like a 2-way table of additive by rating; i.e., the rows are the
four additives and the columns are the nine levels of the rating scale.
*/
title 'Example 3: Ordinal Logistic Regression';
data Cheese;
do Additive = 1 to 4;
do y = 1 to 9;
input freq @@;
output;
end;
end;
label y='Taste Rating';
datalines;
0 0 1 7 8 8 19 8 1
6 9 12 11 7 6 1 0 0
1 1 6 8 23 7 5 1 0
0 0 0 1 3 7 14 16 11
;
proc hplogistic data=Cheese;
freq freq;
class Additive(ref='4') / param=ref ;
model y=Additive;
title 'Multiple Response Cheese Tasting Experiment';
run;