public void KappaTestConstructorTest()
{
// Example from http://vassarstats.net/kappa.html
// Checked against http://graphpad.com/quickcalcs/Kappa2.cfm (OK)
int[,] matrix =
{
{ 44, 5, 1 },
{ 7, 20, 3 },
{ 9, 5, 6 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(a.RowTotals[0], 50);
Assert.AreEqual(a.RowTotals[1], 30);
Assert.AreEqual(a.RowTotals[2], 20);
Assert.AreEqual(a.ColumnTotals[0], 60);
Assert.AreEqual(a.ColumnTotals[1], 30);
Assert.AreEqual(a.ColumnTotals[2], 10);
Assert.AreEqual(0.4915, a.Kappa, 1e-4);
Assert.IsFalse(double.IsNaN(a.Kappa));
double var = a.Variance;
double var0 = a.VarianceUnderNull;
double varD = Accord.Statistics.Testing.KappaTest.DeltaMethodKappaVariance(a);
double se = System.Math.Sqrt(var);
double se0 = System.Math.Sqrt(var0);
double seD = System.Math.Sqrt(varD);
Assert.AreEqual(0.072, a.StandardError, 0.0005);
// Create a test of the null hypothesis (actual k = 0)
KappaTest target = new KappaTest(a, hypothesizedKappa: 0);
// Std. Error is computed differently under the null hypothesis:
Assert.AreEqual(0.073509316753225237, target.StandardError, 1e-5);
Assert.IsFalse(double.IsNaN(target.StandardError));
}
public void KappaTestConstructorTest2()
{
// Example from: M. Reichenheim (2004). Confidence intervals for the
// kappa statistic. The Stata Journal (2004) 4, Number 4, pp. 421–428.
// http://www.stata-journal.com/sjpdf.html?articlenum=st0076
int[,] matrix = // (pg 599)
{
{ 48, 12 },
{ 16, 160 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
// Reichenheim's paper shows:
// Agreement | Expected Agreement | Kappa | Std. Error | Z
// 88.14% | 61.25% | 0.6938 | 0.0650 | 10.67
Assert.AreEqual(88.14, a.OverallAgreement * 100, 1e-2);
Assert.AreEqual(61.25, a.ChanceAgreement * 100, 1e-2);
Assert.AreEqual(0.6938, a.Kappa, 1e-4);
Assert.AreEqual(0.0650, a.StandardErrorUnderNull, 1e-4);
KappaTest target = new KappaTest(a);
Assert.AreEqual(OneSampleHypothesis.ValueIsGreaterThanHypothesis, target.Hypothesis);
Assert.AreEqual(10.67, target.Statistic, 1e-3);
Assert.AreEqual(7.0849733798130419E-27, target.PValue);
}
public void KappaTestConstructorTest5()
{
// Example from Statistical Methods for Rates and Proportions
// for kappa variance under the null hypothesis
// Checked against Statistical Methods for Rates and Proportions (OK)
int[,] matrix = // (pg 599)
{
{ 75, 1, 4 },
{ 5, 4, 1 },
{ 0, 0, 10 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(100, a.Samples);
Assert.AreEqual(80, a.RowTotals[0]);
Assert.AreEqual(10, a.RowTotals[1]);
Assert.AreEqual(10, a.RowTotals[2]);
Assert.AreEqual(80, a.ColumnTotals[0]);
Assert.AreEqual(5, a.ColumnTotals[1]);
Assert.AreEqual(15, a.ColumnTotals[2]);
double[,] proportions = // (pg 599)
{
{ 0.75, 0.01, 0.04 },
{ 0.05, 0.04, 0.01 },
{ 0.00, 0.00, 0.10 },
};
Assert.IsTrue(proportions.IsEqual(a.ProportionMatrix));
// Test under null hypothesis
KappaTest target = new KappaTest(a, hypothesizedKappa: 0,
alternate: OneSampleHypothesis.ValueIsGreaterThanHypothesis);
Assert.AreEqual(0.68, target.EstimatedValue, 0.01); // pg 605
Assert.AreEqual(a.Kappa, target.EstimatedValue);
Assert.IsFalse(double.IsNaN(target.EstimatedValue));
Assert.AreEqual(0.076, target.StandardError, 0.001);
Assert.IsFalse(double.IsNaN(target.StandardError));
Assert.AreEqual(8.95, target.Statistic, 0.08);
Assert.IsTrue(target.Significant);
}
public void KappaTestConstructorTest4()
{
// Example from Statistical Methods for Rates and Proportions
// Checked against http://graphpad.com/quickcalcs/Kappa2.cfm (OK)
// Checked against Statistical Methods for Rates and Proportions (OK)
// Checked against http://vassarstats.net/kappa.html (FAIL)
int[,] matrix = // (pg 599)
{
{ 75, 1, 4 },
{ 5, 4, 1 },
{ 0, 0, 10 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(100, a.Samples);
Assert.AreEqual(80, a.RowTotals[0]);
Assert.AreEqual(10, a.RowTotals[1]);
Assert.AreEqual(10, a.RowTotals[2]);
Assert.AreEqual(80, a.ColumnTotals[0]);
Assert.AreEqual(5, a.ColumnTotals[1]);
Assert.AreEqual(15, a.ColumnTotals[2]);
double[,] proportions = // (pg 599)
{
{ 0.75, 0.01, 0.04 },
{ 0.05, 0.04, 0.01 },
{ 0.00, 0.00, 0.10 },
};
Assert.IsTrue(proportions.IsEqual(a.ProportionMatrix));
double expectedVar = a.Variance;
// Test against non-null hypothesis
KappaTest target = new KappaTest(a, hypothesizedKappa: 0.8);
// Fleiss reports 0.68 (page 606)
// Graphpad reports 0.676
Assert.AreEqual(0.68, target.EstimatedValue, 0.01);
Assert.AreEqual(a.Kappa, target.EstimatedValue);
Assert.IsFalse(double.IsNaN(target.EstimatedValue));
// Fleiss reports 0.087 (page 607)
// Graphpad reports 0.088
Assert.AreEqual(0.087, target.StandardError, 0.001);
Assert.IsFalse(double.IsNaN(target.StandardError));
Assert.AreEqual(-1.38, target.Statistic, 0.029);
Assert.AreEqual(0.1589, target.PValue, 0.0001);
Assert.IsFalse(target.Significant);
}
public void KappaTestConstructorTest()
{
int[,] matrix =
{
{ 44, 5, 1},
{ 7, 20, 3 },
{ 9, 5, 6 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(0.4915, a.Kappa, 1e-4);
Assert.IsFalse(double.IsNaN(a.Kappa));
KappaTest target = new KappaTest(a);
Assert.AreEqual(0.0777, target.StandardError, 1e-2);
Assert.IsFalse(double.IsNaN(target.StandardError));
Assert.AreEqual(0.3393, target.Confidence.Min, 1e-2);
Assert.AreEqual(0.6437, target.Confidence.Max, 1e-2);
}
public void KappaTestConstructorTest3()
{
int[,] matrix =
{
{ 377, 79, 0, 0 },
{ 2, 72, 0, 0 },
{ 33, 5, 60, 0 },
{ 3, 20, 0, 8 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(0.7845, a.OverralAgreement, 1e-4);
Assert.IsFalse(double.IsNaN(a.OverralAgreement));
Assert.AreEqual(0.47986, a.ChanceAgreement, 1e-5);
Assert.IsFalse(double.IsNaN(a.ChanceAgreement));
Assert.AreEqual(0.586, a.Kappa, 1e-3);
Assert.IsFalse(double.IsNaN(a.Kappa));
KappaTest target = new KappaTest(a);
Assert.AreEqual(0.586, target.Kappa, 1e-3);
Assert.AreEqual(a.Kappa, target.Kappa);
Assert.IsFalse(double.IsNaN(target.Kappa));
Assert.AreEqual(0.00087457, target.Variance, 1e-5);
Assert.IsFalse(double.IsNaN(target.Variance));
Assert.AreEqual(19.806, target.Statistic, 0.1);
Assert.IsFalse(double.IsNaN(target.Statistic));
Assert.AreEqual(0.644, target.Confidence.Max, 1e-3);
Assert.AreEqual(0.528, target.Confidence.Min, 1e-3);
Assert.AreEqual(0.0, target.PValue, 1e-6);
Assert.IsFalse(double.IsNaN(target.PValue));
Assert.IsTrue(target.Significant);
}
public void KappaTestConstructorTest2()
{
int[,] matrix =
{
{ 317, 23, 0, 0 },
{ 61, 120, 0, 0 },
{ 2, 4, 60, 0 },
{ 35, 29, 0, 8 },
};
GeneralConfusionMatrix a = new GeneralConfusionMatrix(matrix);
Assert.AreEqual(0.7663, a.OverralAgreement, 1e-4);
Assert.IsFalse(double.IsNaN(a.OverralAgreement));
Assert.AreEqual(0.4087, a.ChanceAgreement, 1e-5);
Assert.IsFalse(double.IsNaN(a.ChanceAgreement));
KappaTest target = new KappaTest(a);
Assert.AreEqual(0.605, target.Kappa, 1e-3);
Assert.AreEqual(a.Kappa, target.Kappa);
Assert.IsFalse(double.IsNaN(target.Kappa));
Assert.AreEqual(0.00073735, target.Variance, 1e-5);
Assert.IsFalse(double.IsNaN(target.Variance));
Assert.AreEqual(22.272, target.Statistic, 0.15);
Assert.IsFalse(double.IsNaN(target.Statistic));
Assert.AreEqual(0.658, target.Confidence.Max, 1e-3);
Assert.AreEqual(0.552, target.Confidence.Min, 1e-3);
Assert.AreEqual(0.0, target.PValue, 1e-6);
Assert.IsFalse(double.IsNaN(target.PValue));
Assert.IsTrue(target.Significant);
}