The QLIM Procedure

Example 22.1 Ordered Data Modeling

Cameron and Trivedi (1986) studied Australian Health Survey data. Variable definitions are given in Cameron and Trivedi (1998, p. 68).

The dependent variable, dvisits, has nine ordered values. The following SAS statements estimate the ordinal probit model:

/*-- Ordered Discrete Responses --*/
proc qlim data=docvisit;
   model dvisits = sex age agesq income levyplus
                   freepoor freerepa illness actdays hscore
                   chcond1 chcond2 / discrete;
run;

The output of the QLIM procedure for ordered data modeling is shown in Output 22.1.1.

By default, ordinal probit/logit models are estimated assuming that the first threshold or limit parameter () is 0. However, this parameter can also be estimated when the LIMIT1=VARYING option is specified. The probability that belongs to the th category is defined as

where is the logistic or standard normal CDF, and . Output 22.1.2 lists ordinal probit estimates computed in the following program. Note that the intercept term is suppressed for model identification when is estimated.

/*-- Ordered Probit --*/
proc qlim data=docvisit;
   model dvisits = sex age agesq income levyplus
                   freepoor freerepa illness actdays hscore
                   chcond1 chcond2 / discrete(d=normal) limit1=varying;
run;