The following section describes scripting-only messages for MANOVA, Generalized Linear Models, Nominal and Ordinal Logistic, and Standard Least Squares.
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( "$SAMPLE_DATA/Dogs.jmp" );
obj = dt << Fit Model(
Y( :LogHist0, :LogHist1, :LogHist3, :LogHist5 ),
Effects( :drug, :dep1, :drug * :dep1 ),
Personality( "Manova" ),
Run( Response Function( Sum ) )
);
obj << (Response[1] << (Effect[1] << Save Canonical Scores) );
The following message for a Fit GLM object is available only in JSL. The message saves the parametric formula to a new column in the data table
Parametric Formula( )
The following messages for Fit Nominal Logistic and Fit Ordinal Logistic objects are available only in JSL:
fit_model_object << Get SAS Data Step
// create a SAS DATA step to score the data
fit_model_object << Get MM SAS Data Step
// create SAS code that you can register in the SAS Model Manager
The following JSL messages return the requested item from the fitted model, such as variance components, p-values, parameter estimates, and so on:
fit_model_object << Get Variance Components( );
fit_model_object << Get Effect Names( );
fit_model_object << Get Effect PValues( );
fit_model_object << Get Estimates( );
fit_model_object << Get Parameter Names( );
fit_model_object << Get Random Effect Names( );
fit_model_object << Get Std Errors( );
fit_model_object << Get X Matrix( );
fit_model_object << Get XPX Inverse( );
fit_model_object << Get Y Matrix( );
The following message for Standard Least Squares objects is available only in JSL:
obj << Get SQL prediction expression;
The following example saves prediction formulas as SQL expressions and outputs them to the log:
dt = Open( "$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;