ANOVAoutliers-windoze.jsl

/*

demoFTest.jsl
02apr2001

Purpose
Demonstrate how changes in the data affect F ratios and associated p-values.

Author
Gerry Hobbs (concept) (West Virginia University)
Wen Hu (prototype)
Mark Bailey (implementation)

Contact
mark.bailey@sas.com

Usage
Simply run this script by any one of these methods:

	Edit > Run Script
	Control-R
	Click "Run Script" button in tool bar

The demoFTest data table is required and opened automatically if it is located in the same directory as the script.

Future Improvement Ideas
Optimize Open() to work with any location and file path.
Add means diamonds to graph.
Generalize to any continuous by nominal or ordinal comparison.

*/

Clear Globals();

dt = Current Data Table();

dlg = Column Dialog(
	yCol = Col List(
		"Y, Response",
		Min Col(1),
		Max Col(1),
		Data Type(Numeric)
	),
	xCol = Col List(
		"X, Factor",
		Min Col(1),
		Max Col(1)
	),
	"Choose variables for one-way ANOVA"
);

If( dlg["Button"] == -1, Throw( "User cancelled" ) );
Remove From( dlg ); Eval List( dlg );

dt << Sort(
	By( xCol[1], yCol[1] ),
	Order( Ascending ),
	Replace Table
);

y = yCol[1] << Get Values;
Summarize(
	group = By( Column( xCol[1] ) ),
	n = Count
);
types = J( N Row( y ), 1, 0 );
For( g = 1, g <= N Items(group), g++,
	r = dt << Get Rows Where( Column( xCol[1] )[] == group[g] );
	types[r] = g;
);

// remove missing values.
r = dt << Get Rows Where( Is Missing( yCol[1][] ) );
For( i = N Row(r), i > 0, i--,
	y[r[i],0] = [];
	types[r[i],0] = [];
);

g = types; // copy used in graph to constrain x values after drag.

n Groups = N Items( group );
xMin = 0;
xMax = n Groups + 1;
yMin = Mean(y) - 6*Std Dev(y);
yMax = Mean(y) + 6*Std Dev(y);

New Window( "Changing P-values",
	H List Box(
		Outline Box( "Oneway ANOVA",
			Graph Box(
				Frame Size( 600, 400 ),
				X Scale( xMin, xMax ),
				Y Scale( yMin, yMax ),
				X Name( Char(xCol[1]) ),
				Y Name( Char(yCol[1]) ),
				Double Buffer,

				x = J( N Row( y ), 1, 1 ) || Design Nom( types );	// design matrix
				a = (x`*x || x`*y) |/ (y`*x || y`*y);			// augmented analysis matrix

				ss Tot = Sweep( a, [1] )[nGroups+1,nGroups+1];	// intercept only
				df Tot = N Row( y ) - 1;
				ms Tot = ss Tot / df Tot;

				ans = Sweep( a, 1::ngroups );				// full model
				ss Error = ans[nGroups+1,nGroups+1];
				df Model = n Groups - 1;
				df Error = df Tot - df Model;
				ms Error = ss Error / df Error;

				ss Model = ss Tot - ss Error;
				ms Model = ss Model / df Model;

				F ratio = ms Model / ms Error;
				p Value = 1 - F Distribution( Abs( F ratio ), df Model, df Error );

				Line Style(1);
				Pen Color(5);
				For( cons = 0; i = 1, i < n Groups, i++,
					H Line( i-0.25, i+0.25, ans[1,nGroups+1] + ans[i+1,nGroups+1] );
					cons += ans[i+1,nGroups+1];
				);
				H Line( i-0.25, i+0.25, ans[1,nGroups+1] - cons );
		
				Line Style(0);
				Pen Color(0);
				H Line( ans[1,nGroups+1] );

				Drag Marker( g, y, g = types );

				tx = xMin + (xMax - xMin) / 20;
				ty = yMin + Round( 0.9 * (yMax - yMin) );
				Text Size(16);
				Text Color(4);
				Text( {tx,ty}, "Mean ", Round( ans[1,nGroups+1], 2 ) );
				ty -= Round( (yMax - yMin) / 25 );
				Text( {tx,ty}, "F ratio ", Round(F ratio, 2) );
				ty -= Round( (yMax - yMin) / 25 );
				Text( {tx,ty}, "P>F ", Round( p Value, 4 ) );
			)
		),
		Outline Box( "Legend",
			Table Box(
				Number Col Box( Char(xCol[1]), 1::ngroups ),
				String Col Box( "Value", group )
			)
		)
	)
);

/*
Revision History (date, change, person)
02apr2001, created, Wen Hu (West Virginia University
17apr2001, adopted JSL Style Guide, incorporate JSL idioms, Mark Bailey
25oct2002, generalize for any ANOVA situation, Sweep, group lines, Mark Bailey
*/

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*/