The RESTRICT statement imposes linear restrictions on the parameter estimates. You can specify any number of RESTRICT statements.

Each restriction is written as an expression, followed by an equality operator (=) or an inequality operator (<, >, <=, >=), followed by a second expression:

The operator can be =, <, >, <= , or >=.

Restriction expressions can be composed of parameters; multiplication (), summation (), and subtraction () operators; and constants. Parameters named in restriction expressions must be among the parameters estimated by the model. Parameters associated with a regressor variable are referred to by the name of the corresponding regressor variable. The restriction expressions must be a linear function of the parameters.

Lagrange multipliers are reported for all the active linear constraints. In the displayed output, the Lagrange multiplier estimates are identified with the names Restrict1, Restrict2, and so on. The probability of the Lagrange multipliers is computed using a beta distribution (LaMotte, 1994).

The following are examples of using the RESTRICT statement:

   proc mdc data=one;
   model y = x1-x10 /
             type=clogit
             choice=(mode 1 2 3);
   id pid;
   restrict x1*2 <= x2 + x3, ;
   run;

   proc mdc data=newdata;
   model decision = ttime /
            type=mprobit
            nchoice=3
            unitvariance=(1 2)
            covest=hess;
   id pid;
   restrict RHO_31 = 0, STD_3<=1;
   run;