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);
}
