Here are some examples of model statements:

• linear regression

  model identity(y) = identity(x);
  

• a linear model with a nonlinear regression function

  model identity(y) = spline(x / nknots=5);
  

• multiple regression

  model identity(y) = identity(x1-x5);
  

• multiple regression with nonlinear transformations

  model spline(y / nknots=3) = spline(x1-x5 / nknots=3);
  

• multiple regression with nonlinear but monotone transformations

  model mspline(y / nknots=3) = mspline(x1-x5 / nknots=3);
  

• multivariate multiple regression

  model identity(y1-y4) = identity(x1-x5);
  

• canonical correlation

  model identity(y1-y4) = identity(x1-x5) / method=canals;
  

• redundancy analysis

  model identity(y1-y4) = identity(x1-x5) / method=redundancy;
  

• preference mapping, vector model (Carroll; 1972)

  model identity(Attrib1-Attrib3) = identity(Dim1-Dim2);
  

• preference mapping, ideal point model (Carroll; 1972)

  model identity(Attrib1-Attrib3) = point(Dim1-Dim2);
  

• preference mapping, ideal point model, elliptical (Carroll; 1972)

  model identity(Attrib1-Attrib3) = epoint(Dim1-Dim2);
  

• preference mapping, ideal point model, quadratic (Carroll; 1972)

  model identity(Attrib1-Attrib3) = qpoint(Dim1-Dim2);
  

• metric conjoint analysis

  model identity(Subj1-Subj50) = class(a b c d e f / zero=sum);
  

• nonmetric conjoint analysis

  model monotone(Subj1-Subj50) = class(a b c d e f / zero=sum);
  

• main effects, two-way interaction

  model identity(y) = class(a|b);
  

• less-than-full-rank model—main effects and two-way interaction are constrained to sum to zero

  model identity(y) = class(a|b / zero=sum);
  

• main effects and all two-way interactions

  model identity(y) = class(a|b|c@2);
  

• main effects and all two- and three-way interactions

  model identity(y) = class(a|b|c);
  

• main effects and only the b*c two-way interaction

  model identity(y) = class(a b c b*c);
  

  
  

• seven main effects, three two-way interactions

  model identity(y) = class(a b c d e f g a*b a*c a*d);
  

• deviations-from-means (effects or ) coding, with an a reference level of ’1’ and a b reference level of ’2’

  model identity(y) = class(a|b / deviations zero='1' '2');
  

• cell-means coding (implicit intercept)

  model identity(y) = class(a*b / zero=none);
  

• reference cell model

  model identity(y) = class(a|b / zero='1' '1');
  

• reference line with change in line parameters

  model identity(y) = class(a) | identity(x);
  

• reference curve with change in curve parameters

  model identity(y) = class(a) | spline(x);
  

• separate curves and intercepts

  model identity(y) = class(a / zero=none) | spline(x);
  

• quantitative effects with interaction

  model identity(y) = identity(x1 | x2);
  

• separate quantitative effects with interaction within each cell

  model identity(y) = class(a * b / zero=none) | identity(x1 | x2);