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fit_model_object << ( Response[1] << (Effect[1] << ... ) );
Test Details // show or hide the test details for an individual effect.
Centroid Plot // show or hide the centroid plot for an individual effect.
Save Canonical Scores // save the canonical scores for an individual effect.
Contrast // run a customized F test contrasting different levels for an effect in the model.
dt = Open( "$SAMPLE_DATA/Dogs.jmp" );
obj = dt << Fit Model(
	Y( :LogHist0, :LogHist1, :LogHist3, :LogHist5 ),
	Effects( :drug, :dep1, :drug * :dep1 ),
	Personality( "Manova" ),
	Run( Response Function( Sum ) )
);
obj << (Response[1] << (Effect[1] << Save Canonical Scores) );
Parametric Formula( )
// save the parametric formula to a new column in the data table
// that is associated with the report
fit_model_object << Get SAS Data Step
fit_model_object << Get MM SAS Data Step
fit_model_object << Get Variance Components( );
fit_model_object << Get Effect Names( );
fit_model_object << Get Effect PValues( );
fit_model_object << Get Estimates( );
fit_model_object << Get Parameter Names( );
fit_model_object << Get Random Effect Names( );
fit_model_object << Get Std Errors( );
fit_model_object << Get X Matrix( );
fit_model_object << Get XPX Inverse( );
fit_model_object << Get Y Matrix( );
obj << Get SQL prediction expression;
dt = Open( "$SAMPLE_DATA/Tiretread.jmp" );
obj = dt << Fit Model(
	Y( :ABRASION, :HARDNESS ),
	Effects( :SILICA, :SILANE, :SULFUR ),
	Personality( "Standard Least Squares" ),
	Run
);
code = obj << Get SQL Prediction Expression;

Help created on 3/19/2020