Represents an analysis of variance (ANOVA) calculation.

Namespace: Extreme.Statistics
Assembly: Extreme.Numerics (Extreme.Numerics)

Syntax

Visual Basic (Declaration)
Public Class OneWayRAnovaModel _
	Inherits AnovaModel
C#
public class OneWayRAnovaModel : AnovaModel
C++
public ref class OneWayRAnovaModel : public AnovaModel

Methods

IconTypeDescription
Compute()
Computes the model.
ComputeModel()
Computes the model.
Contains(GeneralLinearModel)
Returns a value that indicates whether another GeneralLinearModel is nested within this instance.
Equals(Object)
Determines whether the specified Object is equal to the current Object.
Finalize()
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
GetFactor(Int32)
Gets the factor corresponding to the variable with the specified index.
GetFactor(String)
Gets the factor corresponding to the variable with the specified name.
GetHashCode()
Serves as a hash function for a particular type.
GetHomogeneityOfVariancesTest()
Returns a test to verify that the cells have the same variance.
GetHomogeneityOfVariancesTest(TestOfHomogeneityOfVariances)
Returns a test to verify that the cells have the same variance.
GetType()
Gets the Type of the current instance.
MemberwiseClone()
Creates a shallow copy of the current Object.
ResetComputation()
Clears all computed model parameters.
SetAnovaModelRow(Int32, String, Double, Double)
Sets the data of a row in the model's AnovaTable.
SetAnovaRow(AnovaRowType, String, Double, Double)
Sets the data of a row in the model's AnovaTable.
ToString()
Returns a string representation of this instance.

Constructors

IconTypeDescription
OneWayRAnovaModelNew(DataTable, String, String, String)
Constructs a new OneWayRAnovaModel object.
OneWayRAnovaModelNew(NumericalVariable, CategoricalVariable, CategoricalVariable)
Constructs a new OneWayAnovaModel object for the specified data..
OneWayRAnovaModelNew(VariableCollection, String, String, String)
Constructs a new OneWayAnovaModel object for the specified data..

Properties

IconTypeDescription
AdjustedRSquared
Gets the adjusted R Squared value for the regression.
AnovaTable
Gets the AnovaTable that summarizes the results of this model.
BetweenGroupsRow
Gets the AnovaModelRow containing the 'between groups' results.
BetweenSubjectsRow
Gets the AnovaModelRow containing the 'between subjects' results.
Cells
Gets the collection of data cells for this model.
Computed
Gets a value that indicates whether the regression model has been computed.
DegreesOfFreedom
Gets the total degrees of freedom of the data.
DependentVariables
Gets the collection of dependent variables associated with this model.
FStatistic
Gets the F statistic for the regression.
IndependentVariables
Gets the collection of independent variables associated with this model.
IsBalanced
Gets a value that indicates whether this ANOVA design is balanced.
Parameters
Gets the collection of parameters associated with this model.
PValue
Gets the probability corresponding to the F statistic for the regression.
ResidualSumOfSquares
Gets the sum of squares of the residuals of the model.
RSquared
Gets the R Squared value for the regression.
StandardError
Gets the standard error of the regression.

Remarks

Use the OneWayRAnovaModel to represent an analysis of variance model with one factor. The dependent variable, factor variable and subject variable must be specified in the constructor. The dependent variable must be of type NumericalVariable. The factor and subject variables must be of type CategoricalVariable.

OneWayRAnovaModel inherits from AnovaModel, which in turn inherits from GeneralLinearModel. All methods and properties of these classes are available.

Before you can access the results of the analysis, you must call the Compute() method.

The results of the analysis are available through properties of the model object, including FStatistic and PValue. They are summarized in the AnovaTable.

The Cells property returns a CellArray object that represents the data organized into cells. There is one cell for every combination of factor levels. Cell means and other properties of the model can be accessed through the properties of individual cells.

One of the assumptions in analysis of variance is that the variances of the data in each cell are the same. The GetHomogeneityOfVariancesTest() returns a hypothesis test object that allows you to verify this assumption.

Inheritance Hierarchy

System.Object
  Extreme.Statistics.GeneralLinearModel
    Extreme.Statistics.AnovaModel
      Extreme.Statistics.OneWayRAnovaModel

See Also