STATBEAN Name: ANOVA
Purpose: Statgraphics ANOVA software calculates an analysis of variance involving one or more factors. This STATBEAN calculates ANOVA with Java using JavaBeans.
DataSource For Statgraphics ANOVA software: any.
Read/Write Properties
| Name | Type | Description | Possible Values | Default Value |
| cVariableNames | String[] | The names of the columns with data values to be used for any covariates. | Any string. | "" |
| largestInteraction | int | the largest interaction to be estimated. | >=1 | 2 |
| tablewiseExclusion | boolean | Whether all rows of the data table containing a missing value in any column should be excluded from the calculations. | true,false | false |
| tolerance | double | Conditioning tolerance for aborting matrix inversion. | >0 and <=0.000001 | 0.0000000001 |
| xVariableNames | String[] | The names of the columns with data values to be used for the factor (X) variables. | Any string. | "" |
| yVariableName | String | The name of the column with data values to be used for the dependent (Y) variable. | Any string. | "Y" |
Other Public Methods To Use For Statgraphics ANOVA Software
| Name | Description | Arguments | Return Value |
| void excludeInteraction(int factor1,int factor2,boolean exclude) | Excludes a selected interaction. | Number of 1st factor, number of 2nd factor, exclude or not. | None. |
| double getAdjustedRSquared() | Returns the adjusted coefficient of determination. | None. | Adjusted R-squared, or missingValueCode if model cannot be fit. |
| void getDegreesOfFreedom(int df[3]) | Returns the degrees of freedom corresponding to the sums of squares. | Integer output array. | None. |
| void getDF(int df[numberOfEffects]) | Returns the degrees of freedom corresponding to each effect. | Integer output array. | None. |
| double getDurbinWatson() | Returns the Durbin-Watson statistic. | None. | DW, or missingValueCode if model cannot be fit. |
| double getEffectFRatio(int k) | Returns the F-ratio for effect k. | Effect index. | F-ratio. |
| double getEffectPValue(int k) | Returns the P-value for effect k. | Effect index. | P-value. |
| String getFactorString() | Returns string with effect indicators. | None. | Consecutive 8-character strings such as AB identifying each effect. |
| double getGrandMean() | Returns the overall mean. | None. | Grand mean. |
| void getLSMeans(double[numberOfLevels]) | Returns the calculated least squares means for each level. | Double output array. | None. |
| void getLSSigmas(double[numberOfLevels]) | Returns the standard errors of the calculated least squares means for each level. | Double output array. | None. |
| double getMeanAbsoluteError() | Returns the residual mean absolute error. | None. | MAE, or missingValueCode if model cannot be fit. |
| double getMeanSquaredError() | Returns the residual mean squared error. | None. | MSE, or missingValueCode if model cannot be fit. |
| double getModelPValue() | Returns the P-value for the fitted model. | None. | P-value. |
| int getNumberOfLevels() | Returns the number of levels for all main effects and interactions combined. | None. | Number of levels. |
| int getNumberOfEffects() | Returns the number of main effects and interactions. | None. | Number of effects. |
| int getNumberOfFactors() | Returns the number of factors. | None. | Number of factors. |
| void getPredictedValues(double p[n]) | Returns the predicted value of Y corresponding to each row in the datasource. | Double output array. | None. |
| double getResidualDegreesOfFreedom() | Returns the d.f. for the error term used to estimate the standard errors. | None. | Residual df, or 0 if model cannot be fit. |
| void getResiduals(double r[n]) | Returns the residual corresponding to each row in the datasource. | Double output array. | Residual or missingValueCode. |
| double getResidualStandardError() | Returns the estimated standard deviation of the residuals. | None. | Standard error of the estimate, or missingValueCode if model cannot be fit. |
| double getRSquared() | Returns the coefficient of determination. | None. | R-squared, or missingValueCode if model cannot be fit. |
| double getSampleSize() | Returns the number of non-missing data values. | None. | Sample size. |
| void getSumsOfSquares(double ss[3]) | Returns the following sums of squares: total, model, residual. | Double output array. | None. |
| void getTypeISumsOfSquares(double[]) | Returns the reduction in the residual sum of squares as each variable is entered into the model. | Double output array. | None. |
| void getTypeIIISumsOfSquares(double[]) | Returns the reduction in the residual sum of squares if each variable is entered last into the model. | Double output array. | None. |
Output Variables
| Name | Description |
| Predicted | The predicted value of Y corresponding to each row in the datasource. |
| Residual | The residual corresponding to each row in the datasource. |
Other properties are inherited from the general CalculationStatbean class.
Code Sample
//create a datasource bean
FileDataSource fileDataSource1 = new STATBEANS.FileDataSource();
//set the file name to be read
fileDataSource1.setFileName("c:\\statbeans\\samples\\cardata2.txt");
//create a calculation bean
Anova anova1 = new STATBEANS.Anova();
//set the column names
anova1.setYVariableName("mpg");
java.lang.String[] tempString = new String[2];
tempString[0] = "origin";
tempString[1] = "year";
anova1.setXVariableNames(tempString);
//create a table bean
AnovaTable anovaTable1 = new STATBEANS.AnovaTable();
//define the desired elements to display
anovaTable1.setShowANOVA(true);
anovaTable1.setShowDependentVariable(true);
anovaTable1.setShowMeans(true);
anovaTable1.setShowStatistics(false);
//make the calculation bean a listener for changes in the FileDataSource bean
fileDataSource1.addDataChangeListener(anova1.listenerForDataChange);
//make the table bean a listener for changes in the calculation bean
anova1.addDataChangeListener(anovaTable1.listenerForDataChange);
//instruct the fileDataSource bean to read the file
fileDataSource1.readData();
NOTES
Use the excludeFactor method to selectively remove two-factor interactions from the model. For example, to remove interaction AC, execute excludeFactor(1,3,true). Note that when retrieving effect sums of squares, degrees of freedom, F ratios, or P values, positions for the excluded factors remain in the output arrays but should be ignored.
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