public void BonferroniHolmUnitTest2()
{
/* example taken from
* http://en.wikipedia.org/wiki/Holm-Bonferroni_method#Example
*
* p = 0.01, 0.04, 0.03, 0.005
* a = 0.05
* cor_p = 0.03, 0.06, 0.06, 0.02
* h = 1, 0, 0, 1
*
*/
double[] correctedPValues = new double[] { 0.03, 0.06, 0.06, 0.02 };
double[] pVals = new[] { 0.01, 0.04, 0.03, 0.005 };
bool[] h = new bool[] { true, false, false, true };
bool[] decision;
var result = BonferroniHolm.Calculate(0.05, pVals, out decision);
for (int i = 0; i < pVals.Length; i++)
{
Assert.AreEqual(correctedPValues[i], result[i]);
Assert.AreEqual(h[i], decision[i]);
}
}
public void BonferroniHolmUnitTest1()
{
/* example taken from
* http://www.mathworks.com/matlabcentral/fileexchange/28303-bonferroni-holm-correction-for-multiple-comparisons
*
* p = 0.56, 0.22, 0.001, 0.04, 0.01
* a = 0.05
* cor_p = 0.560, 0.440, 0.005, 0.120, 0.040
* h = 0, 0, 1, 0, 1
*
*/
double[] correctedPValues = new double[] { 0.56, 0.44, 0.005, 0.12, 0.04 };
double[] pVals = new[] { 0.56, 0.22, 0.001, 0.04, 0.01 };
bool[] h = new bool[] { false, false, true, false, true };
bool[] decision;
var result = BonferroniHolm.Calculate(0.05, pVals, out decision);
for (int i = 0; i < pVals.Length; i++)
{
Assert.AreEqual(correctedPValues[i], result[i]);
Assert.AreEqual(h[i], decision[i]);
}
}
private void CalculatePairwiseTest(string groupName)
{
var columnNames = stringConvertibleMatrixView.Content.ColumnNames.ToList();
int colIndex = columnNames.IndexOf(groupName);
columnNames = columnNames.Where(x => x != groupName).ToList();
double[][] newData = FilterDataForPairwiseTest(colIndex);
var rowNames = new[] { "p-Value of Mann-Whitney U", "Adjusted p-Value of Mann-Whitney U",
"p-Value of T-Test", "Adjusted p-Value of T-Test", "Cohen's d", "Hedges' g" };
DoubleMatrix pValsMatrix = new DoubleMatrix(rowNames.Length, columnNames.Count());
pValsMatrix.ColumnNames = columnNames;
pValsMatrix.RowNames = rowNames;
double mwuBothTails;
double tTestBothTails;
double[] mwuPValues = new double[newData.Length];
double[] tTestPValues = new double[newData.Length];
bool[] decision = null;
double[] adjustedMwuPValues = null;
double[] adjustedTtestPValues = null;
int cnt = 0;
for (int i = 0; i < newData.Length; i++)
{
mwuBothTails = PairwiseTest.MannWhitneyUTest(data[colIndex], newData[i]);
tTestBothTails = PairwiseTest.TTest(data[colIndex], newData[i]);
mwuPValues[i] = mwuBothTails;
tTestPValues[i] = tTestBothTails;
if (mwuBothTails > significanceLevel)
{
cnt++;
}
}
adjustedMwuPValues = BonferroniHolm.Calculate(significanceLevel, mwuPValues, out decision);
adjustedTtestPValues = BonferroniHolm.Calculate(significanceLevel, tTestPValues, out decision);
for (int i = 0; i < newData.Length; i++)
{
pValsMatrix[0, i] = mwuPValues[i];
pValsMatrix[1, i] = adjustedMwuPValues[i];
pValsMatrix[2, i] = tTestPValues[i];
pValsMatrix[3, i] = adjustedTtestPValues[i];
pValsMatrix[4, i] = SampleSizeDetermination.CalculateCohensD(data[colIndex], newData[i]);
pValsMatrix[5, i] = SampleSizeDetermination.CalculateHedgesG(data[colIndex], newData[i]);
}
Invoke(new Action(() => {
pairwiseStringConvertibleMatrixView.Content = pValsMatrix;
pairwiseStringConvertibleMatrixView.DataGridView.AutoResizeColumns(DataGridViewAutoSizeColumnsMode.AllCells);
}));
ShowPairwiseResult(cnt);
}
public void BonferroniHolmUnitTest3()
{
// comparison with R's p.adjust(p, "holm") method
double[] correctedPValues = new double[] { 0.23262159, 0.05204139 };
double[] pVals = new[] { 0.232621592948806, 0.0260206949805373 };
bool[] decision;
var result = BonferroniHolm.Calculate(0.05, pVals, out decision);
for (int i = 0; i < pVals.Length; i++)
{
Assert.AreEqual(correctedPValues[i], Math.Round(result[i], 8));
}
}
public void BonferroniHolmUnitTest5()
{
// comparison with R's p.adjust(p, "holm") method
double[] correctedPValues = new double[] { 1.389563e-05, 7.293675e-05, 2.330999e-04, 2.330999e-04, 4.370736e-04, 5.539326e-04 };
double[] pVals = new[] { 2.315938e-06, 1.458735e-05, 5.827497e-05, 7.166659e-05, 2.185368e-04, 5.539326e-04 };
bool[] decision;
var result = BonferroniHolm.Calculate(0.05, pVals, out decision);
for (int i = 0; i < pVals.Length; i++)
{
Assert.AreEqual(Math.Round(correctedPValues[i], 10), Math.Round(result[i], 10));
}
}
public void BonferroniHolmUnitTest4()
{
// comparison with R's p.adjust(p, "holm") method
double[] correctedPValues = new double[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
double[] pVals = new[] { 0.1108139, 0.1241641, 0.2805913, 0.3715633, 0.3967397, 0.6165547, 0.7272018, 0.8774432, 0.9495787, 0.9755199 };
bool[] decision;
var result = BonferroniHolm.Calculate(0.05, pVals, out decision);
for (int i = 0; i < pVals.Length; i++)
{
Assert.AreEqual(correctedPValues[i], Math.Round(result[i], 8));
}
}
