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;