Multiple Correspondence Analysis

Example 1

Summary: Generate multiple correspondence analysis

Code:

// Open data table
dt = Open("$Sample_Data/Car Poll.jmp");
// Multiple Correspondence Analysis
Multiple Correspondence Analysis(
    Y(
        :sex, :marital status, :country,
        :size
    ),
    Cross Table(
        Cell Chi Square( 0 ),
        Show Total( 1 )
    )
);

Example 2

Summary: Generate multiple correspondence analysis with a supplementary variable

Code:

// Open data table
dt = Open("$Sample_Data/Car Poll.jmp");
// Multiple Correspondence Analysis - with Supplementary Variable
Multiple Correspondence Analysis(
    Y( :country, :size ),
    Z( :sex ),
    Cross Table(
        Cell Chi Square( 0 ),
        Show Total( 1 )
    ),
    Cross Table of Supplementary Columns(
        Cell Chi Square( 0 ),
        Show Total( 1 )
    )
);

Example 3

Summary: Perform Multiple Correspondence Analysis (MCA) on categorical variables TV, Film, Art, and Restaurant, and display the total cross table.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-level
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    Cross Table( Show Total( 1 ) )
);

Example 4

Summary: Perform Multiple Correspondence Analysis (MCA) on categorical data variables with Subject as the supplementary variable, and generate a cross table with total values shown.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-subject
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    X( :Subject ),
    Cross Table( Show Total( 1 ) )
);

Example 5

Summary: Perform multiple correspondence analysis on categorical data, stratifying by gender, and customize the report display to include supplementary columns and specific dimension selection.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-level-supp-gender
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    Z( :Gender ),
    Cross Table( Show Total( 1 ) ),
    Cross Table of Supplementary Columns(
        Show Total( 1 )
    ),
    Select dimension( 1, 3 ),
    SendToReport(
        Dispatch( {}, "Variable Summary",
            OutlineBox,
            {Close( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "2", ScaleBox,
            {Format( "Fixed Dec", 12, 0 ),
            Min( -2 ), Max( 3.5 ),
            Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "Details", OutlineBox,
            {Close( 1 )}
        )
    )
);

Example 6

Summary: Perform Multiple Correspondence Analysis with supplementary rows for subject and gender, and generate detailed coordinates and scaling for the first three dimensions.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-subject-supp-gender
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    X( :Subject ),
    Z( :Gender ),
    Cross Table( Show Total( 1 ) ),
    Cross Table of Supplementary Rows(
        Show Total( 1 )
    ),
    Show Coordinates( 1 ),
    Select dimension( 1, 3 ),
    SendToReport(
        Dispatch( {}, "Variable Summary",
            OutlineBox,
            {Close( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "2", ScaleBox,
            {Format( "Fixed Dec", 12, 0 ),
            Min( -2 ), Max( 3.5 ),
            Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "Details", OutlineBox,
            {Close( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "Row and Column Coordinates",
            OutlineBox,
            {Close( 1 )}
        )
    )
);

Example 7

Summary: Perform Multiple Correspondence Analysis (MCA) on the given data table, fitting supplementary variables by age.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-level-supp-age
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    Z( :Age ),
    Cross Table( Show Total( 1 ) ),
    Cross Table of Supplementary Columns(
        Show Total( 1 )
    ),
    SendToReport(
        Dispatch( {}, "Variable Summary",
            OutlineBox,
            {Close( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "Details", OutlineBox,
            {Close( 1 )}
        )
    )
);

Example 8

Summary: Perform Multiple Correspondence Analysis (MCA) with 'TV', 'Film', 'Art', and 'Restaurant' as categorical response variables, 'Subject' as a supplementary row variable, and 'Age' as a supplementary column variable, and visualize the results in a 2D plot.

Code:

// Open data table
dt = Open("$Sample_Data/Employee Taste.jmp");
// MCA-subject-supp-age
Multiple Correspondence Analysis(
    Y( :TV, :Film, :Art, :Restaurant ),
    X( :Subject ),
    Z( :Age ),
    Cross Table( Show Total( 1 ) ),
    Cross Table of Supplementary Rows(
        Show Total( 1 )
    ),
    Select dimension( 1, 3 ),
    SendToReport(
        Dispatch( {}, "Variable Summary",
            OutlineBox,
            {Close( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "2", ScaleBox,
            {Format( "Fixed Dec", 12, 0 ),
            Min( -2 ), Max( 3.5 ),
            Inc( 1 ), Minor Ticks( 1 )}
        ),
        Dispatch(
            {"Correspondence Analysis"},
            "Details", OutlineBox,
            {Close( 1 )}
        )
    )
);

Example 9

Summary: Perform Multiple Correspondence Analysis on a dataset with Year as the dependent variable, Region and ID as supplementary variables, and Population as the frequency variable, including chi-square measures and totals in the cross tables.

Code:

// Open data table
dt = Open("$Sample_Data/US Regional Population.jmp");
// Multiple Correspondence Analysis
Multiple Correspondence Analysis(
    Y( :Year ),
    X( :Region ),
    Freq( :Population ),
    Supplementary ID( :ID ),
    Cross Table(
        Cell Chi Square( 0 ),
        Show Total( 1 )
    ),
    Cross Table of Supplementary Rows(
        Cell Chi Square( 0 ),
        Show Total( 1 )
    )
);