Fit Model Script-Only Messages

The following section describes scripting-only messages for MANOVA, Generalized Linear Models, Nominal and Ordinal Logistic, and Standard Least Squares.

MANOVA

The following message for a Fit MANOVA object is available only in JSL:

fit_model_object << ( Response[1] << (Effect[1] << ... ) );

Where the third message could be one of the following:

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*/

The following example saves canonical scores for the Response Function, which in this data, is Sum:

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) );

Generalized Linear Models

The following message for a Fit GLM object is available only in JSL. The message saves the parametric formula to a new column in the data table

Parametric Formula( )

Nominal and Ordinal Logistic

The following messages for Fit Nominal Logistic and Fit Ordinal Logistic objects are available only in JSL:

// create a SAS DATA step to score the data

fit_model_object << Get SAS Data Step

// create SAS code that you can register in the SAS Model Manager

fit_model_object << Get MM SAS Data Step

Standard Least Squares

The following JSL messages return the requested item from the fitted model, such as variance components, p-values, parameter estimates, and so on:

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( );

The following message for Standard Least Squares objects is available only in JSL:

obj << Get SQL prediction expression;

The following example saves prediction formulas as SQL expressions and outputs them to the log:

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;

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